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.

ARM/GCSS/SPARC TWP-ICE CRM Intercomparison Study

NASA Technical Reports Server (NTRS)

Fridlind, Ann; Ackerman, Andrew; Petch, Jon; Field, Paul; Hill, Adrian; McFarquhar, Greg; Xie, Shaocheng; Zhang, Minghua

2010-01-01

Specifications are provided for running a cloud-resolving model (CRM) and submitting results in a standardized format for inclusion in a n intercomparison study and archiving for public access. The simulated case study is based on measurements obtained during the 2006 Tropical Warm Pool - International Cloud Experiment (TWP-ICE) led by the U. S. department of Energy Atmospheric Radiation Measurement (ARM) program. The modeling intercomparison study is based on objectives developed in concert with the Stratospheric Processes And their Role in Climate (SPARC) program and the GEWEX cloud system study (GCSS) program. The Global Energy and Water Cycle Experiment (GEWEX) is a core project of the World Climate Research PRogramme (WCRP).

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.;

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.

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.

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.

A Numerical Study of Tropical Sea-Air Interactions Using a Cloud Resolving Model Coupled with an Ocean Mixed-Layer Model

NASA Technical Reports Server (NTRS)

Shie, Chung-Lin; Tao, Wei-Kuo; Johnson, Dan; Simpson, Joanne; Li, Xiaofan; Sui, Chung-Hsiung; Einaudi, Franco (Technical Monitor)

2001-01-01

Coupling a cloud resolving model (CRM) with an ocean mixed layer (OML) model can provide a powerful tool for better understanding impacts of atmospheric precipitation on sea surface temperature (SST) and salinity. The objective of this study is twofold. First, by using the three dimensional (3-D) CRM-simulated (the Goddard Cumulus Ensemble model, GCE) diabatic source terms, radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the OML model, the respective impact of individual component on upper ocean heat and salt budgets are investigated. Secondly, a two-way air-sea interaction between tropical atmospheric climates (involving atmospheric radiative-convective processes) and upper ocean boundary layer is also examined using a coupled two dimensional (2-D) GCE and OML model. Results presented here, however, only involve the first aspect. Complete results will be presented at the conference.

Vertical overlap of probability density functions of cloud and precipitation hydrometeors: CLOUD AND PRECIPITATION PDF OVERLAP

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

Ovchinnikov, Mikhail; Lim, Kyo-Sun Sunny; Larson, Vincent E.

Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continentalmore » and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.« less

Improving Representation of Convective Transport for Scale-Aware Parameterization, Part II: Analysis of Cloud-Resolving Model Simulations

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

Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.

2015-04-27

Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the mid-latitude continental and the tropical regions are conducted and evaluated, we examine the scale-dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraftmore » eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of 38 mid-latitude continental convection. We show that the single updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as 3 updrafts can account for the internal variability of updrafts well. Based on evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.« less

Climate Simulations from Super-parameterized and Conventional General Circulation Models with a Third-order Turbulence Closure

NASA Astrophysics Data System (ADS)

Xu, Kuan-Man; Cheng, Anning

2014-05-01

A high-resolution cloud-resolving model (CRM) embedded in a general circulation model (GCM) is an attractive alternative for climate modeling because it replaces all traditional cloud parameterizations and explicitly simulates cloud physical processes in each grid column of the GCM. Such an approach is called "Multiscale Modeling Framework." MMF still needs to parameterize the subgrid-scale (SGS) processes associated with clouds and large turbulent eddies because circulations associated with planetary boundary layer (PBL) and in-cloud turbulence are unresolved by CRMs with horizontal grid sizes on the order of a few kilometers. A third-order turbulence closure (IPHOC) has been implemented in the CRM component of the super-parameterized Community Atmosphere Model (SPCAM). IPHOC is used to predict (or diagnose) fractional cloudiness and the variability of temperature and water vapor at scales that are not resolved on the CRM's grid. This model has produced promised results, especially for low-level cloud climatology, seasonal variations and diurnal variations (Cheng and Xu 2011, 2013a, b; Xu and Cheng 2013a, b). Because of the enormous computational cost of SPCAM-IPHOC, which is 400 times of a conventional CAM, we decided to bypass the CRM and implement the IPHOC directly to CAM version 5 (CAM5). IPHOC replaces the PBL/stratocumulus, shallow convection, and cloud macrophysics parameterizations in CAM5. Since there are large discrepancies in the spatial and temporal scales between CRM and CAM5, IPHOC used in CAM5 has to be modified from that used in SPCAM. In particular, we diagnose all second- and third-order moments except for the fluxes. These prognostic and diagnostic moments are used to select a double-Gaussian probability density function to describe the SGS variability. We also incorporate a diagnostic PBL height parameterization to represent the strong inversion above PBL. The goal of this study is to compare the simulation of the climatology from these three models (CAM5, CAM5-IPHOC and SPCAM-IPHOC), with emphasis on low-level clouds and precipitation. Detailed comparisons of scatter diagrams among the monthly-mean low-level cloudiness, PBL height, surface relative humidity and lower tropospheric stability (LTS) reveal the relative strengths and weaknesses for five coastal low-cloud regions among the three models. Observations from CloudSat and CALIPSO and ECMWF Interim reanalysis are used as the truths for the comparisons. We found that the standard CAM5 underestimates cloudiness and produces small cloud fractions at low PBL heights that contradict with observations. CAM5-IPHOC tends to overestimate low clouds but the ranges of LTS and PBL height variations are most realistic. SPCAM-IPHOC seems to produce most realistic results with relatively consistent results from one region to another. Further comparisons with other atmospheric environmental variables will be helpful to reveal the causes of model deficiencies so that SPCAM-IPHOC results will provide guidance to the other two models.

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2002-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and incoming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a cloud-resolving model, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. Dr. Joanne Simpson played a central role in GCE modeling developments and applications. She was the lead author or co-author on more than forty GCE modeling papers. In this paper, a brief discussion and review of the application of the GCE model to (1) cloud interactions and mergers, (2) convective and stratiform interaction, (3) mechanisms of cloud-radiation interaction, (4) latent heating profiles and TRMM, and (5) responses of cloud systems to large-scale processes are provided. Comparisons between the GCE model's results, other cloud-resolving model results and observations are also examined.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Arctic Mixed-phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity to Microphysics Parameterizations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Luo, Yali; Morrison, Hugh; Mcfarquhar, G.M.

2008-01-01

Single-layer mixed-phase stratiform (MPS) Arctic clouds, which formed under conditions of large surface heat flux combined with general subsidence during a subperiod of the Atmospheric Radiation Measurement (ARM) Program Mixed-Phase Arctic Cloud Experiment (M-PACE), are simulated with a cloud resolving model (CRM). The CRM is implemented with either an advanced two-moment (M05) or a commonly used one-moment (L83) bulk microphysics scheme and a state-of-the-art radiative transfer scheme. The CONTROL simulation, that uses the M05 scheme and observed aerosol size distribution and ice nulei (IN) number concentration, reproduces the magnitudes and vertical structures of cloud liquid water content (LWC), total ice water content (IWC), number concentration and effective radius of cloud droplets as suggested by the M-PACE observations. It underestimates ice crystal number concentrations by an order of magnitude and overestimates effective radius of ice crystals by a factor of 2-3. The OneM experiment, that uses the L83 scheme, produces values of liquid water path (LWP) and ice plus snow water path (ISWP) that were about 30% and 4 times, respectively, of those produced by the CONTROL. Its vertical profile of IWC exhibits a bimodal distribution in contrast to the constant distribution of IWC produced in the CONTROL and observations.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Tropical convection is one of the main drivers of the climate system and recognized as a major source of uncertainty in climate models. High-resolution modeling is performed with a focus on the deep convection cases during the active monsoon period of the TWP-ICE field campaign to explore ways to improve the fidelity of convection permitting tropical simulations. Cloud resolving model (CRM) simulations are performed with WRF modified to apply flexible configurations for LES/CRM simulations. We have enhanced the capability of the forcing module to test different implementations of large-scale vertical advective forcing, including a function for optional use of large-scale thermodynamic profiles and a function for the condensate advection. The baseline 3D CRM configurations are, following Fridlind et al. (2012), driven by observationally-constrained ARM forcing and tested with diagnosed surface fluxes and fixed sea-surface temperature and prescribed aerosol size distributions. After the spin-up period, the simulations follow the observed precipitation peaks associated with the passages of precipitation systems. Preliminary analysis shows that the simulation is generally not sensitive to the treatment of the large-scale vertical advection of heat and moisture, while more noticeable changes in the peak precipitation rate are produced when thermodynamic profiles above the boundary layer were nudged to the reference profiles from the forcing dataset. The presentation will explore comparisons with observationally-based metrics associated with convective characteristics and examine the model performance with a focus on model physics, doubly-periodic vs. nested configurations, and different forcing procedures/sources. A radar simulator will be used to understand possible uncertainties in radar-based retrievals of convection properties. Fridlind, A. M., et al. (2012), A comparison of TWP-ICE observational data with cloud-resolving model results, J. Geophys. Res., 117, D05204, doi:10.1029/2011JD016595.

Application of advanced data assimilation techniques to the study of cloud and precipitation feedbacks in the tropical climate system

NASA Astrophysics Data System (ADS)

Posselt, Derek J.

The research documented in this study centers around two topics: evaluation of the response of precipitating cloud systems to changes in the tropical climate system, and assimilation of cloud and precipitation information from remote-sensing platforms. The motivation for this work proceeds from the following outstanding problems: (1) Use of models to study the response of clouds to perturbations in the climate system is hampered by uncertainties in cloud microphysical parameterizations. (2) Though there is an ever-growing set of available observations, cloud and precipitation assimilation remains a difficult problem, particularly in the tropics. (3) Though it is widely acknowledged that cloud and precipitation processes play a key role in regulating the Earth's response to surface warming, the response of the tropical hydrologic cycle to climate perturbations remains largely unknown. The above issues are addressed in the following manner. First, Markov chain Monte Carlo (MCMC) methods are used to quantify the sensitivity of the NASA Goddard Cumulus Ensemble (GCE) cloud resolving model (CRM) to changes in its cloud odcrnpbymiC8l parameters. TRMM retrievals of precipitation rate, cloud properties, and radiative fluxes and heating rates over the South China Sea are then assimilated into the GCE model to constrain cloud microphysical parameters to values characteristic of convection in the tropics, and the resulting observation-constrained model is used to assess the response of the tropical hydrologic cycle to surface warming. The major findings of this study are the following: (1) MCMC provides an effective tool with which to evaluate both model parameterizations and the assumption of Gaussian statistics used in optimal estimation procedures. (2) Statistics of the tropical radiation budget and hydrologic cycle can be used to effectively constrain CRM cloud microphysical parameters. (3) For 2D CRM simulations run with and without shear, the precipitation efficiency of cloud systems increases with increasing sea surface temperature, while the high cloud fraction and outgoing shortwave radiation decrease.

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.;

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

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

NASA Technical Reports Server (NTRS)

Cheng, Anning; Xu, Kuan-Man

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

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.

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.

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

DOE PAGES

Jung, Joon -Hee

2016-10-11

Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

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

Jung, Joon -Hee

Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less

Simulation of orographic effects with a Quasi-3-D Multiscale Modeling Framework: Basic algorithm and preliminary results

NASA Astrophysics Data System (ADS)

Jung, Joon-Hee

2016-12-01

The global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of the topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.

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.

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

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David (Technical Monitor)

2002-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Diagnosing the Ice Crystal Enhancement Factor in the Tropics

NASA Technical Reports Server (NTRS)

Zeng, Xiping; Tao, Wei-Kuo; Matsui, Toshihisa; Xie, Shaocheng; Lang, Stephen; Zhang, Minghua; Starr, David O'C; Li, Xiaowen; Simpson, Joanne

2009-01-01

Recent modeling studies have revealed that ice crystal number concentration is one of the dominant factors in the effect of clouds on radiation. Since the ice crystal enhancement factor and ice nuclei concentration determine the concentration, they are both important in quantifying the contribution of increased ice nuclei to global warming. In this study, long-term cloud-resolving model (CRM) simulations are compared with field observations to estimate the ice crystal enhancement factor in tropical and midlatitudinal clouds, respectively. It is found that the factor in tropical clouds is 10 3-104 times larger than that of mid-latitudinal ones, which makes physical sense because entrainment and detrainment in the Tropics are much stronger than in middle latitudes. The effect of entrainment/detrainment on the enhancement factor, especially in tropical clouds, suggests that cloud microphysical parameterizations should be coupled with subgrid turbulence parameterizations within CRMs to obtain a more accurate depiction of cloud-radiative forcing.

A Multi-scale Modeling System: Developments, Applications and Critical Issues

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa;

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.

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.

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.

Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2015-04-01

Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this cycle system under a zero-dimensional configuration. Preliminary simulations of this cycle system over a two-dimensional domain will be presented.

Explicit prediction of ice clouds in general circulation models

NASA Astrophysics Data System (ADS)

Kohler, Martin

1999-11-01

Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted) and falling snow (diagnosed) components. An empirical parameterization of the effect of upward turbulent water fluxes in cloud layers is obtained from the CRM simulations by (1) identifying the time-scale of conversion of cloud ice to snow as the key parameter, and (2) regressing it onto cloud differential IR heating and environmental static stability. The updated UCLA-GCM achieves close agreement with observations in global mean top of atmosphere fluxes (within 1--4 W/m2). Artificially suppressing the impact of cloud turbulent fluxes reduces the global mean ice water path by a factor of 3 and produces errors in each of solar and IR fluxes at the top of atmosphere of about 5--6 W/m2.

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.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

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 CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

NASA Astrophysics Data System (ADS)

Keller, Michael; Kröner, Nico; Fuhrer, Oliver; Lüthi, Daniel; Schmidli, Juerg; Stengel, Martin; Stöckli, Reto; Schär, Christoph

2018-04-01

Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM) and 2 km grid spacing (convection-resolving model, CRM) are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW) using a vertically uniform warming and the other with vertically dependent warming (VW) that enables changes in lapse rate. The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.

Resolution-dependent behavior of subgrid-scale vertical transport in the Zhang-McFarlane convection parameterization

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

Xiao, Heng; Gustafson, Jr., William I.; Hagos, Samson M.

2015-04-18

With this study, to better understand the behavior of quasi-equilibrium-based convection parameterizations at higher resolution, we use a diagnostic framework to examine the resolution-dependence of subgrid-scale vertical transport of moist static energy as parameterized by the Zhang-McFarlane convection parameterization (ZM). Grid-scale input to ZM is supplied by coarsening output from cloud-resolving model (CRM) simulations onto subdomains ranging in size from 8 × 8 to 256 × 256 km 2s.

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

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.

Validation of Model Simulations of Anvil Cirrus Properties During TWP-ICE: Final Report

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

Zipser, Edward J.

2013-05-20

This 3-year grant, with two extensions, resulted in a successful 5-year effort, led by Ph.D. student Adam Varble, to compare cloud resolving model (CRM) simulations with the excellent database obtained during the TWP-ICE field campaign. The objective, largely achieved, is to undertake these comparisons comprehensively and quantitatively, informing the community in ways that goes beyond pointing out errors in the models, but points out ways to improve both cloud dynamics and microphysics parameterizations in future modeling efforts. Under DOE support, Adam Varble, with considerable assistance from Dr. Ann Fridlind and others, entrained scientists who ran some 10 different CRMs andmore » 4 different limited area models (LAMs) using a variety of microphysics parameterizations, to ensure that the conclusions of the study will have considerable generality.« less

Joint ARM/GCSS/SPARC TWP-ICE CRM Intercomparison Study: Description, Preliminary Results, and Invitation to Participate

NASA Astrophysics Data System (ADS)

Fridlind, A. M.; Ackerman, A. S.; Allen, G.; Beringer, J.; Comstock, J. M.; Field, P. R.; Gallagher, M.; Hacker, J. M.; Hume, T.; Jakob, C.; Liu, G.; Long, C. N.; Mather, J. H.; May, P. T.; McCoy, R. F.; McFarlane, S. A.; McFarquhar, G. M.; Minnis, P.; Petch, J. C.; Schumacher, C.; Turner, D. D.; Whiteway, J. A.; Williams, C. R.; Williams, P. I.; Xie, S.; Zhang, M.

2008-12-01

The 2006 Tropical Warm Pool - International Cloud Experiment (TWP-ICE) is 'the first field program in the tropics that attempted to describe the evolution of tropical convection, including the large-scale heat, moisture, and momentum budgets at 3-hourly time resolution, while at the same time obtaining detailed observations of cloud properties and the impact of the clouds on the environment' [May et al., 2008]. A cloud- resolving model (CRM) intercomparison based on TWP-ICE is now being undertaken by the Atmospheric Radiation Measurement (ARM), GEWEX Cloud Systems Study (GCSS), and Stratospheric Processes And their Role in Climate (SPARC) programs. We summarize the 16-day case study and the wealth of data being used to provide initial and boundary conditions, and evaluate some preliminary findings in the context of existing theories of moisture evolution in the tropical tropopause layer (TTL). Overall, simulated cloud fields evolve realistically by many measures. Budgets indicate that simulated convective flux convergence of water vapor is always positive or near zero at TTL elevations, except locally at lower levels during the driest suppressed monsoon conditions, while simulated water vapor deposition to hydrometeors always exceeds sublimation on average at all TTL elevations over 24-hour timescales. The next largest water vapor budget term is generally the nudging required to keep domain averages consistent with observations, which is at least partly attributable to large-scale forcing terms that cannot be derived from measurements. We discuss the primary uncertainties.

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

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 ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.

Exploring the potential of machine learning to break deadlock in convection parameterization

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Gentine, P.

2017-12-01

We explore the potential of modern machine learning tools (via TensorFlow) to replace parameterization of deep convection in climate models. Our strategy begins by generating a large ( 1 Tb) training dataset from time-step level (30-min) output harvested from a one-year integration of a zonally symmetric, uniform-SST aquaplanet integration of the SuperParameterized Community Atmosphere Model (SPCAM). We harvest the inputs and outputs connecting each of SPCAM's 8,192 embedded cloud-resolving model (CRM) arrays to its host climate model's arterial thermodynamic state variables to afford 143M independent training instances. We demonstrate that this dataset is sufficiently large to induce preliminary convergence for neural network prediction of desired outputs of SP, i.e. CRM-mean convective heating and moistening profiles. Sensitivity of the machine learning convergence to the nuances of the TensorFlow implementation are discussed, as well as results from pilot tests from the neural network operating inline within the SPCAM as a replacement to the (super)parameterization of convection.

Overlap Properties of Clouds Generated by a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Khairoutdinov, M.

2002-01-01

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

Boundary-layer diabatic processes, the virtual effect, and convective self-aggregation

NASA Astrophysics Data System (ADS)

Yang, D.

2017-12-01

The atmosphere can self-organize into long-lasting large-scale overturning circulations over an ocean surface with uniform temperature. This phenomenon is referred to as convective self-aggregation and has been argued to be important for tropical weather and climate systems. Here we use a 1D shallow water model and a 2D cloud-resolving model (CRM) to show that boundary-layer diabatic processes are essential for convective self-aggregation. We will show that boundary-layer radiative cooling, convective heating, and surface buoyancy flux help convection self-aggregate because they generate available potential energy (APE), which sustains the overturning circulation. We will also show that evaporative cooling in the boundary layer (cold pool) inhibits convective self-aggregation by reducing APE. Both the shallow water model and CRM results suggest that the enhanced virtual effect of water vapor can lead to convective self-aggregation, and this effect is mainly in the boundary layer. This study proposes new dynamical feedbacks for convective self-aggregation and complements current studies that focus on thermodynamic feedbacks.

Simulating the 2012 High Plains Drought Using Three Single Column Models (SCM)

NASA Astrophysics Data System (ADS)

Medina, I. D.; Baker, I. T.; Denning, S.; Dazlich, D. A.

2015-12-01

The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited, and have used conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we focus on the 2012 High Plains drought and perform numerical simulations using three single column model (SCM) versions of BUGS5 (Colorado State University (CSU) GCM coupled to the Simple Biosphere Model (SiB3)). In the first version of BUGS5, the model is used in its standard bulk setting (single atmospheric column coupled to a single instance of SiB3), secondly, the Super-Parameterized Community Atmospheric Model (SP-CAM), a cloud resolving model (CRM) (CRM consists of 32 atmospheric columns), replaces the single CSU GCM atmospheric parameterization and is coupled to a single instance of SiB3, and for the third version of BUGS5, an instance of SiB3 is coupled to each CRM column of the SP-CAM (32 CRM columns coupled to 32 instances of SiB3). To assess the physical realism of the land-atmosphere feedbacks simulated by all three versions of BUGS5, differences in simulated energy and moisture fluxes are computed between the 2011 and 2012 period and are compared to those calculated using observational data from the AmeriFlux Tower Network for the same period at the ARM Site in Lamont, OK. This research will provide a better understanding of model deficiencies in reproducing and predicting droughts in the future, which is essential to the economic, ecologic and social well being of the High Plains.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

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. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Significant Features Found in Simulated Tropical Climates Using a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Simpson, J.; Sui, C.-H.

2000-01-01

Cloud resolving model (CRM) has widely been used in recent years for simulations involving studies of radiative-convective systems and their role in determining the tropical regional climate. The growing popularity of CRMs usage can be credited for their inclusion of crucial and realistic features such like explicit cloud-scale dynamics, sophisticated microphysical processes, and explicit radiative-convective interaction. For example, by using a two-dimensional cloud model with radiative-convective interaction process, found a QBO-like (quasibiennial oscillation) oscillation of mean zonal wind that affected the convective system. Accordingly, the model-generated rain band corresponding to convective activity propagated in the direction of the low-level zonal mean winds; however, the precipitation became "localized" (limited within a small portion of the domain) as zonal mean winds were removed. Two other CRM simulations by S94 and Grabowski et al. (1996, hereafter G96), respectively that produced distinctive quasi-equilibrium ("climate") states on both tropical water and energy, i.e., a cold/dry state in S94 and a warm/wet state in G96, have later been investigated by T99. They found that the pattern of the imposed large-scale horizontal wind and the magnitude of the imposed surface fluxes were the two crucial mechanisms in determining the tropical climate states. The warm/wet climate was found associated with prescribed strong surface winds, or with maintained strong vertical wind shears that well-organized convective systems prevailed. On the other hand, the cold/dry climate was produced due to imposed weak surface winds and weak wind shears throughout a vertically mixing process by convection. In this study, considered as a sequel of T99, the model simulations to be presented are generally similar to those of T99 (where a detailed model setup can be found), except for a more detailed discussion along with few more simulated experiments. There are twelve major experiments chosen for presentations that are introduced in section two. Several significant feature analyses regarding the rainfall properties, CAPE (Convective Available Potential Energy), cloud-scale eddies, the stability issue, the convective system propagation, relative humidity, and the effect on the quasi-equilibrium state by the imposed constant. radiation or constant surface fluxes, and etc. will be presented in the meeting. However, only three of the subjects are discussed in section three. A brief summary is concluded in the end section.

Convective Systems Over the Japan Sea: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Yoshizaki, Masanori; Shie, Chung-Lin; Kato, Teryuki

2002-01-01

Wintertime observations of MCSs (Mesoscale Convective Systems) over the Sea of Japan - 2001 (WMO-01) were collected from January 12 to February 1, 2001. One of the major objectives is to better understand and forecast snow systems and accompanying disturbances and the associated key physical processes involved in the formation and development of these disturbances. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, wind profilers, radiometers, etc.) during WMO-01 provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with winter storms over the Sea of Japan region. WMO-01 also provided estimates of the apparent heat source (Q1) and apparent moisture sink (Q2). The vertical integrals of Q1 and Q2 are equal to the surface precipitation rates. The horizontal and vertical adjective components of Q1 and Q2 can be used as large-scale forcing for the Cloud Resolving Models (CRMs). The Goddard Cumulus Ensemble (GCE) model is a CRM (typically run with a 1-km grid size). The GCE model has sophisticated microphysics and allows explicit interactions between clouds, radiation, and surface processes. It will be used to understand and quantify precipitation processes associated with wintertime convective systems over the Sea of Japan (using data collected during the WMO-01). This is the first cloud-resolving model used to simulate precipitation processes in this particular region. The GCE model-simulated WMO-01 results will also be compared to other GCE model-simulated weather systems that developed during other field campaigns (i.e., South China Sea, west Pacific warm pool region, eastern Atlantic region and central USA).

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W. K.; Wang, Y.; Qian, J.; Shie, C. -L.; Lau, W. K. -M.; Kakar, R.; Starr, David O' C. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration

DOE PAGES

Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.; ...

2016-05-01

The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less

Macroscopic Relationships among Latent Heating, Precipitation, Organized Convection and the Environment

NASA Technical Reports Server (NTRS)

Moncrieff, Mitchell W.; Liu, Changhai

2002-01-01

Three-dimensional Cloud Resolving Model (CRM) simulations were conducted to examine the squall line observed on 26 January, 1999 from the Tropical Rainfall Measuring Mission Large Scale Biosphere Atmosphere Experiment in Amazonia (TRMM-LBA) field campaign. The computational domain was 600 kilometers x 180 kilometers x 20 kilometers with a horizontal resolution of 1 kilometer and a vertical resolution of 200 meters. The CRM was initialized from the Abracos Hill and Rebio soundings. Convection was initiated by a surface-based and NW-SE oriented cold pool over a region 60 kilometers in the y-direction and 30 kilometers wide in the x-direction. The cold pool temperature perturbation is a maximum of -6K at the surface, decreasing linearly to zero at 3 kilometers. The simulated convection is in the form of a NW-SE band that moves toward the southwest at a speed of 8 meters per second, and is generally comparable to radar observations.

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

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.

The Role of Atmospheric Aerosol Concentration on Deep Convective Precipitation: Cloud-resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Li, X.; Khain, A.; Mastsui, T.; Lang, S.; Simpson, J.

2007-01-01

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 20011. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. ln this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific. In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection.

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.

Progress in the Development of a Global Quasi-3-D Multiscale Modeling Framework

NASA Astrophysics Data System (ADS)

Jung, J.; Konor, C. S.; Randall, D. A.

2017-12-01

The Quasi-3-D Multiscale Modeling Framework (Q3D MMF) is a second-generation MMF, which has following advances over the first-generation MMF: 1) The cloud-resolving models (CRMs) that replace conventional parameterizations are not confined to the large-scale dynamical-core grid cells, and are seamlessly connected to each other, 2) The CRMs sense the three-dimensional large- and cloud-scale environment, 3) Two perpendicular sets of CRM channels are used, and 4) The CRMs can resolve the steep surface topography along the channel direction. The basic design of the Q3D MMF has been developed and successfully tested in a limited-area modeling framework. Currently, global versions of the Q3D MMF are being developed for both weather and climate applications. The dynamical cores governing the large-scale circulation in the global Q3D MMF are selected from two cube-based global atmospheric models. The CRM used in the model is the 3-D nonhydrostatic anelastic Vector-Vorticity Model (VVM), which has been tested with the limited-area version for its suitability for this framework. As a first step of the development, the VVM has been reconstructed on the cubed-sphere grid so that it can be applied to global channel domains and also easily fitted to the large-scale dynamical cores. We have successfully tested the new VVM by advecting a bell-shaped passive tracer and simulating the evolutions of waves resulted from idealized barotropic and baroclinic instabilities. For improvement of the model, we also modified the tracer advection scheme to yield positive-definite results and plan to implement a new physics package that includes a double-moment microphysics and an aerosol physics. The interface for coupling the large-scale dynamical core and the VVM is under development. In this presentation, we shall describe the recent progress in the development and show some test results.

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: 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.

Spectral Retrieval of Latent Heating Profiles from TRMM PR data. Part 3; Moistening Estimates over Tropical Ocean Regions

NASA Technical Reports Server (NTRS)

Shige, S.; Takayabu, Y.; Tao, W.-K.

2007-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of precipitation formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the tropics with the associated latent heating (LH) accounting for threefourths of the total heat energy available to the Earth's atmosphere. In the last decade, it has been established that standard products of LH from satellite measurements, particularly TRMM measurements, would be a valuable resource for scientific research and applications. Such products would enable new insights and investigations concerning the complexities of convection system life cycles, the diabatic heating controls and feedbacks related to rne-sosynoptic circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations In environmental prediction models. However, the LH and water vapor profile or budget (called the apparent moisture sink, or Q2) is closely related. This paper presented the development of an algorithm for retrieving Q2 using 'TRMM precipitation radar. Since there is no direct measurement of LH and Q2, the validation of algorithm usually applies a method called consistency check. Consistency checking involving Cloud Resolving Model (CRM)-generated LH and 42 profiles and algorithm-reconstructed is a useful step in evaluating the performance of a given algorithm. In this process, the CRM simulation of a time-dependent precipitation process (multiple-day time series) is used to obtain the required input parameters for a given algorithm. The algorithm is then used to "econsti-LKth"e heating and moisture profiles that the CRM simulation originally produced, and finally both sets of conformal estimates (model and algorithm) are compared each other. The results indicate that discrepancies between the reconstructed and CM-simulated profiles for Q2, especially at low levels, are larger than those for latent heat. Larger discrepancies in Q2 at low levels are due to moistening for non-precipitating region that algorithm cannot reconstruct. Nevertheless, the algorithm-reconstructed total Q2 profiles are in good agreement with the CRM-simulated ones.

Relating Convective and Stratiform Rain to Latent Heating

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Stephen; Zeng, Xiping; Shige, Shoichi; Takayabu, Yukari

2010-01-01

The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate-high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.58 horizontal resolution, the occurrence of conditional rain rates over 100 mm/day is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations. An improved convective-stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.

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

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.;

The impact of mesoscale convective systems on global precipitation: A modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo

2017-04-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. Typical MCSs have horizontal scales of a few hundred kilometers (km); therefore, a large domain and high resolution are required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) with 32 CRM grid points and 4 km grid spacing also might not have sufficient resolution and domain size for realistically simulating MCSs. In this study, the impact of MCSs on precipitation processes is examined by conducting numerical model simulations using the Goddard Cumulus Ensemble model (GCE) and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with less grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show that the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are either weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures (SSTs) is conducted and results in both reduced surface rainfall and evaporation.

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-06-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

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

NASA Astrophysics Data System (ADS)

Panosetti, Davide; Schlemmer, Linda; Schär, Christoph

2018-05-01

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

Time-Resolved Emission Spectroscopy of Field Reversed Configuration Thruster

DTIC Science & Technology

2016-08-31

radiation Collection Optics to 600um fiber Source: Scharer Research Group Source: PEARL 1. Acquire Spectrum 2. Compare to Collisional‐Radiative Model ( CRM ...calibration (deuterium lamp) • Obtain Argon FRC data and use Collisional Radiative Model ( CRM ) to extract plasma properties • Apply knowledge to improve FRC

A strategy for representing the effects of convective momentum transport in multiscale models: Evaluation using a new superparameterized version of the Weather Research and Forecast model (SP-WRF)

NASA Astrophysics Data System (ADS)

Tulich, S. N.

2015-06-01

This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

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

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

Investigation of hydrometeor classification uncertainties through the POLARRIS polarimetric radar simulator

NASA Astrophysics Data System (ADS)

Dolan, B.; Rutledge, S. A.; Barnum, J. I.; Matsui, T.; Tao, W. K.; Iguchi, T.

2017-12-01

POLarimetric Radar Retrieval and Instrument Simulator (POLARRIS) is a framework that has been developed to simulate radar observations from cloud resolving model (CRM) output and subject model data and observations to the same retrievals, analysis and visualization. This framework not only enables validation of bulk microphysical model simulated properties, but also offers an opportunity to study the uncertainties associated with retrievals such as hydrometeor classification (HID). For the CSU HID, membership beta functions (MBFs) are built using a set of simulations with realistic microphysical assumptions about axis ratio, density, canting angles, size distributions for each of ten hydrometeor species. These assumptions are tested using POLARRIS to understand their influence on the resulting simulated polarimetric data and final HID classification. Several of these parameters (density, size distributions) are set by the model microphysics, and therefore the specific assumptions of axis ratio and canting angle are carefully studied. Through these sensitivity studies, we hope to be able to provide uncertainties in retrieved polarimetric variables and HID as applied to CRM output. HID retrievals assign a classification to each point by determining the highest score, thereby identifying the dominant hydrometeor type within a volume. However, in nature, there is rarely just one a single hydrometeor type at a particular point. Models allow for mixing ratios of different hydrometeors within a grid point. We use the mixing ratios from CRM output in concert with the HID scores and classifications to understand how the HID algorithm can provide information about mixtures within a volume, as well as calculate a confidence in the classifications. We leverage the POLARRIS framework to additionally probe radar wavelength differences toward the possibility of a multi-wavelength HID which could utilize the strengths of different wavelengths to improve HID classifications. With these uncertainties and algorithm improvements, cases of convection are studied in a continental (Oklahoma) and maritime (Darwin, Australia) regime. Observations from C-band polarimetric data in both locations are compared to CRM simulations from NU-WRF using the POLARRIS framework.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

We are developing synthetic spaceborne radar data toward a simulation of the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core-satellite. Our purposes are a production of test-bed data for higher level DPR algorithm developers, in addition to a diagnosis of a cloud resolving model (CRM). To make the synthetic data, we utilize the CRM by the Japan Meteorological Agency (JMA-NHM) (Ikawa and Saito 1991, Saito et al. 2006, 2007), and the spaceborne radar simulation algorithm by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) named as the Integrated Satellite Observation Simulator for Radar (ISOSIM-Radar). The ISOSIM-Radar simulates received power data in a field of view of the spaceborne radar with consideration to a scan angle of the radar (Oouchi et al. 2002, Kubota et al. 2009). The received power data are computed with gaseous and hydrometeor attenuations taken into account. The backscattering and extinction coefficients are calculated assuming the Mie approximation for all species. The dielectric constants for solid particles are computed by the Maxwell-Garnett model (Bohren and Battan 1982). Drop size distributions are treated in accordance with those of the JMA-NHM. We assume a spherical sea surface, a Gaussian antenna pattern, and 49 antenna beam directions for scan angles from -17 to 17 deg. in the PR. In this study, we report the diagnosis of the JMA-NHM with reference to the TRMM Precipitation Radar (PR) and CloudSat Cloud Profiling Radar (CPR) using the ISOSIM-Radar from the view of comparisons in cloud microphysics schemes of the JMA-NHM. We tested three kinds of explicit bulk microphysics schemes based on Lin et al. (1983), that is, three-ice 1-moment scheme, three-ice 2-moment scheme (Eito and Aonashi 2009), and newly developed four-ice full 2-moment scheme (Hashimoto 2008). The hydrometeor species considered here are rain, graupel, snow, cloud water, cloud ice and hail (4-ice scheme only). We examined a case of an intersection with the TRMM PR and the CloudSat CPR on 6th April 2008 over sea surface in the south of Kyushu Island of Japan. In this work, observed rainfall systems are simulated with one-way double nested domains having horizontal grid sizes of 5 km (outer) and 2 km (inner). Data used here are from the inner domain only. Results of the PR indicated better performances of 2-moment bulk schemes. It suggests that prognostic number concentrations of frozen hydrometeors are more effective in high altitudes and constant number concentrations can lead to the overestimation of the snow there. For three-ice schemes, simulated received power data overestimated above freezing levels with reference to the observed data. In contrast, the overestimation of frozen particles was heavily reduced for the four-ice scheme.

CRYSTAL-FACE Analysis and Simulations of the July 23rd Extended Anvil Case

NASA Technical Reports Server (NTRS)

Starr, David

2003-01-01

A key focus of CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers - Florida Area Cirrus Experiment) was the generation and subsequent evolution of cirrus outflow from deep convective cloud systems. Present theoretical background and motivations will be discussed. An integrated look at the observations of an extended cirrus anvil cloud system observed on 23 July 2002 will be presented, including lidar and millimeter radar observation; from NASA s ER-2 and in-situ observations from NASA s WB-57 and University of North Dakota Citation. The observations will be compared to results of simulations using 1-D and 2-D high-resolution (100 meter) cloud resolving models. The CRMs explicitly account for cirrus microphysical development by resolving the evolving ice crystal size distribution (bin model) in time and space. Both homogeneous and heterogeneous nucleation are allowed in the model. The CRM simulations are driven using the output of regional simulations using MM5 that produces deep convection similar to what was observed. The MM5 model employs a 2 km inner grid (32 layers) over a 360 km domain, nested within a 6-km grid over a 600-km domain. Initial and boundary conditions for the 36-hour MM5 simulation are taken from NCEP Eta model analysis at 32 km resolution. Key issues to be explored are the settling of the observed anvil versus the model simulations, and comparisons of dynamical properties, such as vertical motions, occurring in the observations and models. The former provides an integrated measure of the validity of the model microphysics (fallspeed) while the latter is the key factor in forcing continued ice generation.

Effects of Convective Aggregation on Radiative Cooling and Precipitation in a CRM

NASA Astrophysics Data System (ADS)

Naegele, A. C.; Randall, D. A.

2017-12-01

In the global energy budget, the atmospheric radiative cooling (ARC) is approximately balanced by latent heating, but on regional scales, the ARC and precipitation rates are inversely related. We use a cloud-resolving model to explore how the relationship between precipitation and the ARC is affected by convective aggregation, in which the convective activity is confined to a small portion of the domain that is surrounded by a much larger region of dry, subsiding air. Sensitivity tests show that the precipitation rate and ARC are highly sensitive to both SST and microphysics; a higher SST and 1-moment microphysics both act to increase the domain-averaged ARC and precipitation rates. In all simulations, both the domain-averaged ARC and precipitation rates increased due to convective aggregation, resulting in a positive temporal correlation. Furthermore, the radiative effect of clouds in these simulations is to decrease the ARC. This finding is consistent with our observational results of the cloud effect on the ARC, and has implications for convective aggregation and the geographic extent in which it can occur.

Using the Weak-Temperature Gradient Approximation to Evaluate Parameterizations: An Example of the Transition From Suppressed to Active Convection

NASA Astrophysics Data System (ADS)

Daleu, C. L.; Plant, R. S.; Woolnough, S. J.

2017-10-01

Two single-column models are fully coupled via the weak-temperature gradient approach. The coupled-SCM is used to simulate the transition from suppressed to active convection under the influence of an interactive large-scale circulation. The sensitivity of this transition to the value of mixing entrainment within the convective parameterization is explored. The results from these simulations are compared with those from equivalent simulations using coupled cloud-resolving models. Coupled-column simulations over nonuniform surface forcing are used to initialize the simulations of the transition, in which the column with suppressed convection is forced to undergo a transition to active convection by changing the local and/or remote surface forcings. The direct contributions from the changes in surface forcing are to induce a weakening of the large-scale circulation which systematically modulates the transition. In the SCM, the contributions from the large-scale circulation are dominated by the heating effects, while in the CRM the heating and moistening effects are about equally divided. A transition time is defined as the time when the rain rate in the dry column is halfway to the value at equilibrium after the transition. For the control value of entrainment, the order of the transition times is identical to that obtained in the CRM, but the transition times are markedly faster. The locally forced transition is strongly delayed by a higher entrainment. A consequence is that for a 50% higher entrainment the transition times are reordered. The remotely forced transition remains fast while the locally forced transition becomes slow, compared to the CRM.

Coupling with ocean mixed layer leads to intraseasonal variability in tropical deep convection: Evidence from cloud-resolving simulations

NASA Astrophysics Data System (ADS)

Anber, Usama; Wang, Shuguang; Sobel, Adam

2017-03-01

The effect of coupling a slab ocean mixed layer to atmospheric convection is examined in cloud-resolving model (CRM) simulations in vertically sheared and unsheared environments without Coriolis force, with the large-scale circulation parameterized using the Weak Temperature Gradient (WTG) approximation. Surface fluxes of heat and moisture as well as radiative fluxes are fully interactive, and the vertical profile of domain-averaged horizontal wind is strongly relaxed toward specified profiles with vertical shear that varies from one simulation to the next. Vertical wind shear is found to play a critical role in the simulated behavior. There exists a threshold value of the shear strength above which the coupled system develops regular oscillations between deep convection and dry nonprecipitating states, similar to those found earlier in a much more idealized model which did not consider wind shear. The threshold value of the vertical shear found here varies with the depth of the ocean mixed layer. The time scale of the spontaneously generated oscillations also varies with mixed layer depth, from 10 days with a 1 m deep mixed layer to 50 days with a 10 m deep mixed layer. The results suggest the importance of the interplay between convection organized by vertical wind shear, radiative feedbacks, large-scale dynamics, and ocean mixed layer heat storage in real intraseasonal oscillations.

The Role of Atmospheric Aerosol Concentration on Deep Convective Precipitation: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

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

2010-01-01

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on Clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. In this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific, In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection. The model results suggest that evaporative cooling is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example,, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN.

DDDAS-based Resilient Cyberspace (DRCS)

DTIC Science & Technology

2016-08-03

Resilient Middleware ( CRM ), Supervisor VMs (SVMs), and Master VMs (MVMs). In what follows, we briefly highlight the main functions to be provided by each...phases. 4.5.1.2 Cloud Resilient Middleware ( CRM ) The CRM provides the control and management services to deploy and configure the software and...To speedup the process of selecting the appropriate resilient algorithms and execution environments, the CRM repository contains a set of SBE

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.

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

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 1: Deep Convective Updraft Properties

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

Varble, A. C.; Zipser, Edward J.; Fridlind, Ann

2014-12-27

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias.more » Snow reflectivity can exceed 40 dBZ in a two-moment scheme when a constant bulk density of 100 kg m-3 is used. Making snow mass more realistically proportional to area rather than volume should somewhat alleviate this problem. Graupel, unlike snow, produces high biased reflectivity in all simulations. This is associated with large amounts of liquid water above the freezing level in updraft cores. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of large rainwater contents lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. Strong simulated updraft cores are nearly undiluted, with some showing supercell characteristics. Decreasing horizontal grid spacing from 900 meters to 100 meters weakens strong updrafts, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may partly be a product of interactions between convective dynamics, parameterized microphysics, and large-scale environmental biases that promote different convective modes and strengths than observed.« less

Various Numerical Applications on Tropical Convective Systems Using a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Simpson, J.

2003-01-01

In recent years, increasing attention has been given to cloud resolving models (CRMs or cloud ensemble models-CEMs) for their ability to simulate the radiative-convective system, which plays a significant role in determining the regional heat and moisture budgets in the Tropics. The growing popularity of CRM usage can be credited to its inclusion of crucial and physically relatively realistic features such as explicit cloud-scale dynamics, sophisticated microphysical processes, and explicit cloud-radiation interaction. On the other hand, impacts of the environmental conditions (for example, the large-scale wind fields, heat and moisture advections as well as sea surface temperature) on the convective system can also be plausibly investigated using the CRMs with imposed explicit forcing. In this paper, by basically using a Goddard Cumulus Ensemble (GCE) model, three different studies on tropical convective systems are briefly presented. Each of these studies serves a different goal as well as uses a different approach. In the first study, which uses more of an idealized approach, the respective impacts of the large-scale horizontal wind shear and surface fluxes on the modeled tropical quasi-equilibrium states of temperature and water vapor are examined. In this 2-D study, the imposed large-scale horizontal wind shear is ideally either nudged (wind shear maintained strong) or mixed (wind shear weakened), while the minimum surface wind speed used for computing surface fluxes varies among various numerical experiments. For the second study, a handful of real tropical episodes (TRMM Kwajalein Experiment - KWAJEX, 1999; TRMM South China Sea Monsoon Experiment - SCSMEX, 1998) have been simulated such that several major atmospheric characteristics such as the rainfall amount and its associated stratiform contribution, the Qlheat and Q2/moisture budgets are investigated. In this study, the observed large-scale heat and moisture advections are continuously applied to the 2-D model. The modeled cloud generated from such an approach is termed continuously forced convection or continuous large-scale forced convection. A third study, which focuses on the respective impact of atmospheric components on upper Ocean heat and salt budgets, will be presented in the end. Unlike the two previous 2-D studies, this study employs the 3-D GCE-simulated diabatic source terms (using TOGA COARE observations) - radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the Ocean mixed-layer (OML) model.

The Impact of the Diurnal Cycle of Clouds and Precipitation over the Maritime Continent on the Propagation of the MJO into the Western Pacific

NASA Astrophysics Data System (ADS)

Burleyson, C. D.; Hagos, S. M.; Feng, Z.

2016-12-01

The processes that determine the interaction between the islands of the maritime continent (MC) and the eastward propagation of the Madden-Julian Oscillation (MJO) are poorly understood. We are undertaking a series of observational and modeling analyses aimed at understanding how clouds and precipitation over the islands of the MC lead to changes in the intensity of the MJO (inferred by the amplitude of the Real-time Multivariate MJO index [RMM] and other metrics) as it crosses the MC. One component of our analysis uses the long-term measurements from the DOE Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) to examine cloud radiative effects as the MJO crosses the MC. Using the multi-year ARM dataset and a cloud resolving model (CRM), we show that the MJO interacts with the diurnal cycle of surface heating, clouds, and precipitation over the islands of the MC in a way that weakens it. Additionally, using a satellite climatology based on the TRMM 3B42 dataset we found that MJO episodes that weaken as they cross the MC are characterized by more frequent precipitation and warmer sea surface temperatures (SSTs) south of the equator and less frequent precipitation north of the equator compared to cases where the MJO intensifies. The north-south polarity in SSTs suggests a seasonal dependence in the ability of the MJO to cross the MC. This seasonality was confirmed by looking the seasonal distribution of changes in MJO amplitude as it crosses the MC. Consistent with the SST result, we found that MJO episodes that intensify as they cross the MC are more likely to occur during the northern hemisphere summer and less likely to occur during the northern hemisphere winter (Fig. 1). A regional CRM and satellite observations are used jointly to explore the processes responsible for this seasonality and to examine the impact of interannual oscillations such as ENSO and monsoons on the ability of the MJO to cross the MC. Fig. 1. The annual distribution of the day of the year when the MJO approaches the MC for cases where the RMM amplitude decreases (black lines) and increases (orange lines) across the MC.

Comments on "The Sensitivity Study of Radiative-Convective Equilibrium in the Tropics with a Convective Resolving Model"

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Simpson, J.

2000-01-01

In general, there are two broad scientific objectives when using cloud resolving models (CRMs or cloud ensemble models-CEMs) to study tropical convection. The first one is to use them as a physics resolving models to understand the dynamic and microphysical processes associated with the tropical water and energy cycles and their role in the climate system. The second approach is to use the CRMs to improve the representation of moist processes and their interaction with radiation in large-scale models. In order to improve the credibility of the CRMs and achieve the above goals, CRMs using identical initial conditions and large-scale influences need to produce very similar results. Two CRMs produced different statistical equilibrium (SE) states even though both used the same initial thermodynamic and wind conditions. Sensitivity tests to identify the major physical processes that determine the SE states for the different CRM simulations were performed. Their results indicated that atmospheric horizontal wind is treated quite differently in these two CRMs. The model that had stronger surface winds and consequently larger latent and sensible heat fluxes from the ocean produced a warmer and more humid modeled thermodynamic SE state. In addition, the domain mean thermodynamic state is more unstable for those experiments that produced a warmer and more humid SE state. Their simulated wet (warm and humid) SE states are thermally more stable in the lower troposphere (from the surface to 4-5 km in altitude). The large-scale horizontal advective effects on temperature and water vapor mixing ratio are needed when using CRMs to perform long-term integrations to study convective feedback under specified large-scale environments. In addition, it is suggested that the dry and cold SE state simulated was caused by enhanced precipitation but not enough surface evaporation. We find some problems with the interpretation of these three phenomena.

Simulating the 2012 High Plains drought using three single column versions (SCM) of BUGS5

NASA Astrophysics Data System (ADS)

Medina, I. D.; Denning, S.

2013-12-01

The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited, and have used conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we will focus on the 2012 High Plains drought and will perform numerical simulations using three single column versions (SCM) of BUGS5 (Colorado State University (CSU) GCM coupled to the Simple Biosphere Model (SiB3)) at multiple sites overlying the Ogallala Aquifer for the 2011-2012 periods. In the first version of BUGS5, the model will be used in its standard bulk setting (single atmospheric column coupled to a single instance of SiB3), secondly, the Super-Parameterized Community Atmospheric Model (SP-CAM), a cloud resolving model (CRM consists of 64 atmospheric columns), will replace the single CSU GCM atmospheric parameterization and will be coupled to a single instance of SiB3, and for the third version of BUGS5, an instance of SiB3 will be coupled to each CRM column of the SP-CAM (64 CRM columns coupled to 64 instances of SiB3). To assess the physical realism of the land-atmosphere feedbacks simulated at each site by all versions of BUGS5, differences in simulated energy and moisture fluxes will be computed between the 2011 and 2012 period and will be compared to differences calculated using observational data from the AmeriFlux tower network for the same period. These results will give some insight to the land-atmosphere feedbacks GCMs may produce when atmospheric and land surface heterogeneity are included within a single framework. Furthermore, this research will provide a better understanding of model deficiencies in reproducing and predicting droughts in the future, which is essential to the economic, ecologic and social well being of the High Plains.

The Impact of Simulated Mesoscale Convective Systems on Global Precipitation: A Multiscale Modeling Study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-01-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. In this study, the impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE) model and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Aerosol Radiative Effects on Deep Convective Clouds and Associated Radiative Forcing

NASA Technical Reports Server (NTRS)

Fan, J.; Zhang, R.; Tao, W.-K.; Mohr, I.

2007-01-01

The aerosol radiative effects (ARE) on the deep convective clouds are investigated by using a spectral-bin cloud-resolving model (CRM) coupled with a radiation scheme and an explicit land surface model. The sensitivity of cloud properties and the associated radiative forcing to aerosol single-scattering albedo (SSA) are examined. The ARE on cloud properties is pronounced for mid-visible SSA of 0.85. Relative to the case excluding the ARE, cloud fraction and optical depth decrease by about 18% and 20%, respectively. Cloud droplet and ice particle number concentrations, liquid water path (LWP), ice water path (IWP), and droplet size decrease significantly when the ARE is introduced. The ARE causes a surface cooling of about 0.35 K and significantly high heating rates in the lower troposphere (about 0.6K/day higher at 2 km), both of which lead to a more stable atmosphere and hence weaker convection. The weaker convection and the more desiccation of cloud layers explain the less cloudiness, lower cloud optical depth, LWP and IWP, smaller droplet size, and less precipitation. The daytime-mean direct forcing induced by black carbon is about 2.2 W/sq m at the top of atmosphere (TOA) and -17.4 W/sq m at the surface for SSA of 0.85. The semi-direct forcing is positive, about 10 and 11.2 W/sq m at the TOA and surface, respectively. Both the TOA and surface total radiative forcing values are strongly negative for the deep convective clouds, attributed mostly to aerosol indirect forcing. Aerosol direct and semi-direct effects are very sensitive to SSA. Because the positive semi-direct forcing compensates the negative direct forcing at the surface, the surface temperature and heat fluxes decrease less significantly with the increase of aerosol absorption (decreasing SSA). The cloud fraction, optical depth, convective strength, and precipitation decrease with the increase of absorption, resulting from a more stable and dryer atmosphere due to enhanced surface cooling and atmospheric heating.

A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications. Part 1; Model Formulation and Comparison with Observations

NASA Technical Reports Server (NTRS)

Olson, William S.; Bauer, Peter; Viltard, Nicolas F.; Johnson, Daniel E.; Tao, Wei-Kuo

2000-01-01

In this study, a 1-D steady-state microphysical model which describes the vertical distribution of melting precipitation particles is developed. The model is driven by the ice-phase precipitation distributions just above the freezing level at applicable gridpoints of "parent" 3-D cloud-resolving model (CRM) simulations. It extends these simulations by providing the number density and meltwater fraction of each particle in finely separated size categories through the melting layer. The depth of the modeled melting layer is primarily determined by the initial material density of the ice-phase precipitation. The radiative properties of melting precipitation at microwave frequencies are calculated based upon different methods for describing the dielectric properties of mixed phase particles. Particle absorption and scattering efficiencies at the Tropical Rainfall Measuring Mission Microwave Imager frequencies (10.65 to 85.5 GHz) are enhanced greatly for relatively small (approx. 0.1) meltwater fractions. The relatively large number of partially-melted particles just below the freezing level in stratiform regions leads to significant microwave absorption, well-exceeding the absorption by rain at the base of the melting layer. Calculated precipitation backscatter efficiencies at the Precipitation Radar frequency (13.8 GHz) increase in proportion to the particle meltwater fraction, leading to a "bright-band" of enhanced radar reflectivities in agreement with previous studies. The radiative properties of the melting layer are determined by the choice of dielectric models and the initial water contents and material densities of the "seeding" ice-phase precipitation particles. Simulated melting layer profiles based upon snow described by the Fabry-Szyrmer core-shell dielectric model and graupel described by the Maxwell-Garnett water matrix dielectric model lead to reasonable agreement with radar-derived melting layer optical depth distributions. Moreover, control profiles that do not contain mixed-phase precipitation particles yield optical depths that are systematically lower than those observed. Therefore, the use of the melting layer model to extend 3-D CRM simulations appears justified, at least until more realistic spectral methods for describing melting precipitation in high-resolution, 3-D CRM's are implemented.

Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 1. Deep convective updraft properties: Eval. of TWP-ICE CRMs and LAMs Pt. 1

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

Varble, Adam; Zipser, Edward J.; Fridlind, Ann M.

2014-12-18

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias.more » Making snow mass more realistically proportional to D2 rather than D3 eliminates unrealistically large snow reflectivities over 40 dBZ in some simulations. Graupel, unlike snow, produces high biased reflectivity in all simulations, which is partly a result of parameterized microphysics, but also partly a result of overly intense simulated updrafts. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of liquid condensate, often rain, lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. The strongest simulated updraft cores are nearly undiluted, with some of the strongest showing supercell characteristics during the multicellular (pre-squall) stage of the event. Decreasing horizontal grid spacing from 900 to 100 meters slightly weakens deep updraft vertical velocity and moderately decreases the amount of condensate aloft, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may additionally be a product of unrealistic interactions between convective dynamics, parameterized microphysics, and the large-scale model forcing that promote different convective strengths than observed.« less

The Impact of Model Configuration and Large-Scale, Upper-Level Forcing on CRM-Simulated Convective Systems

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Zeng, X.; Shie, C.-L.; Starr, D.; Simpson, J.

2004-01-01

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, see a brief review by Tao 2003). 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, at NOAA GFDL, at the U. K. Met. Office, at Colorado State University and at NASA Goddard Space Flight Center (Tao 2003). At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (September 1-7, 1974), SCSMEX (June 2-11, 1998), ARM (June 26-30, 1997) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 km domain (with 2-kilometer resolution). The results indicate that surface precipitation and latent heating profiles are similar between the 2D and 3D GCE model simulations. However, there are difference in radiation, surface fluxes and precipitation characteristics. The 2D GCE model was used to perform a long-term integration on ARM/GCSS case 4 (22 days at the ARM southern Great Plains site in March 2000). Preliminary results showed a large temperature bias in the upper troposphere that had not been seen in previous tropical cases. The major objectives of this paper are: (1) to determine the sensitivities to model configuration (ie., 2D in west-east, south-north or 3D), (2) to identify the differences and similarities in the organization and entrainment rates of convection between 2D- and 3D-simulated ARM cloud systems, and (3) assess the impact of upper tropospheric forcing on tropical and ARM case 4 cases.

The Impact of Model Configuration and Large-Scale, Upper-Level Forcing on CRM- Simulated Convective Systems

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Zeng, X.; Shie, C.-L.; Starr, D.; Simpson, J.

2004-01-01

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, see a brief review by Tao 2003). 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, at NOAA GFDL, at the U. K. Met. Office, at Colorado State University and at NASA Goddard Space Flight Center (Tao 2003). At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (September 1-7, 1974), SCSMEX (June 2-11, 1998), ARM (June 26-30, 1997) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 by 512 km domain (with 2-km resolution). The results indicate that surface precipitation and latent heating profiles are similar between the 2D and 3D GCE model simulations. However, there are difference in radiation, surface fluxes and precipitation characteristics. The 2D GCE model was used to perform a long-term integration on ARM/GCSS case 4 (22 days at the ARM Southern Great Plains site in March 2000). Preliminary results showed a large temperature bias in the upper troposphere that had not been seen in previous tropical cases. The major objectives of this paper are: (1) to determine the sensitivities to model configuration (i.e., 2D in west-east, south-north or 3D), (2) to identify the differences and similarities in the organization and entrainment rates of convection between 2D- and 3D-simulated ARM cloud systems, and (3) assess the impact of upper tropospheric forcing on tropical and ARM case 4 cases.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Convective and Stratiform Precipitation Processes and their Relationship to Latent Heating

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Steve; Zeng, Xiping; Shige, Shoichi; Takayabu, Yukari

2009-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. An improved convective -stratiform heating (CSH) algorithm has been developed to obtain the 3D structure of cloud heating over the Tropics based on two sources of information: 1) rainfall information, namely its amount and the fraction due to light rain intensity, observed directly from the Precipitation Radar (PR) on board the TRMM satellite and 2) synthetic cloud physics information obtained from cloud-resolving model (CRM) simulations of cloud systems. The cloud simulations provide details on cloud processes, specifically latent heating, eddy heat flux convergence and radiative heating/cooling, that. are not directly observable by satellite. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. One of the major differences between new and old algorithms is that the level of maximum cloud heating occurs 1 to 1.5 km lower in the atmosphere in the new algorithm. This can effect the structure of the implied air currents associated with the general circulation of the atmosphere in the Tropics. The new CSH algorithm will be used provide retrieved heating data to other heating algorithms to supplement their performance.

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Hou, A.; Lin, X.

2006-01-01

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.