Evaluation of Warm-Rain Microphysical Parameterizations in Cloudy Boundary Layer Transitions

NASA Astrophysics Data System (ADS)

Nelson, K.; Mechem, D. B.

2014-12-01

Common warm-rain microphysical parameterizations used for marine boundary layer (MBL) clouds are either tuned for specific cloud types (e.g., the Khairoutdinov and Kogan 2000 parameterization, "KK2000") or are altogether ill-posed (Kessler 1969). An ideal microphysical parameterization should be "unified" in the sense of being suitable across MBL cloud regimes that include stratocumulus, cumulus rising into stratocumulus, and shallow trade cumulus. The recent parameterization of Kogan (2013, "K2013") was formulated for shallow cumulus but has been shown in a large-eddy simulation environment to work quite well for stratocumulus as well. We report on our efforts to implement and test this parameterization into a regional forecast model (NRL COAMPS). Results from K2013 and KK2000 are compared with the operational Kessler parameterization for a 5-day period of the VOCALS-REx field campaign, which took place over the southeast Pacific. We focus on both the relative performance of the three parameterizations and also on how they compare to the VOCALS-REx observations from the NOAA R/V Ronald H. Brown, in particular estimates of boundary-layer depth, liquid water path (LWP), cloud base, and area-mean precipitation rate obtained from C-band radar.

Spectral cumulus parameterization based on cloud-resolving model

NASA Astrophysics Data System (ADS)

Baba, Yuya

2018-02-01

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

New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Lau, William (Technical Monitor)

2002-01-01

Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).

Stochastic Convection Parameterizations

NASA Technical Reports Server (NTRS)

Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios

2012-01-01

computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts

CloudSat 2C-ICE product update with a new Ze parameterization in lidar-only region.

PubMed

Deng, Min; Mace, Gerald G; Wang, Zhien; Berry, Elizabeth

2015-12-16

The CloudSat 2C-ICE data product is derived from a synergetic ice cloud retrieval algorithm that takes as input a combination of CloudSat radar reflectivity ( Z e ) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation lidar attenuated backscatter profiles. The algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content, and ice particle effective radius in ice or mixed-phase clouds. Because of the nature of the measurements and to maintain consistency in the algorithm numerics, we choose to parameterize (with appropriately large specification of uncertainty) Z e and lidar attenuated backscatter in the regions of a cirrus layer where only the lidar provides data and where only the radar provides data, respectively. To improve the Z e parameterization in the lidar-only region, the relations among Z e , extinction, and temperature have been more thoroughly investigated using Atmospheric Radiation Measurement long-term millimeter cloud radar and Raman lidar measurements. This Z e parameterization provides a first-order estimation of Z e as a function extinction and temperature in the lidar-only regions of cirrus layers. The effects of this new parameterization have been evaluated for consistency using radiation closure methods where the radiative fluxes derived from retrieved cirrus profiles compare favorably with Clouds and the Earth's Radiant Energy System measurements. Results will be made publicly available for the entire CloudSat record (since 2006) in the most recent product release known as R05.

The Influence of Microphysical Cloud Parameterization on Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Gasiewski, Albin J.; Wang, James R.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.

Modelling heterogeneous ice nucleation on mineral dust and soot with parameterizations based on laboratory experiments

NASA Astrophysics Data System (ADS)

Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.

2016-12-01

Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.

Comparison of Ice Cloud Particle Sizes Retrieved from Satellite Data Derived from In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.

A scheme for parameterizing ice cloud water content in general circulation models

NASA Technical Reports Server (NTRS)

Heymsfield, Andrew J.; Donner, Leo J.

1989-01-01

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

NASA Technical Reports Server (NTRS)

Welch, R. M.

1995-01-01

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

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

Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.

A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have beenmore » implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

Modeling of the Wegener Bergeron Findeisen process—implications for aerosol indirect effects

NASA Astrophysics Data System (ADS)

Storelvmo, T.; Kristjánsson, J. E.; Lohmann, U.; Iversen, T.; Kirkevåg, A.; Seland, Ø.

2008-10-01

A new parameterization of the Wegener-Bergeron-Findeisen (WBF) process has been developed, and implemented in the general circulation model CAM-Oslo. The new parameterization scheme has important implications for the process of phase transition in mixed-phase clouds. The new treatment of the WBF process replaces a previous formulation, in which the onset of the WBF effect depended on a threshold value of the mixing ratio of cloud ice. As no observational guidance for such a threshold value exists, the previous treatment added uncertainty to estimates of aerosol effects on mixed-phase clouds. The new scheme takes subgrid variability into account when simulating the WBF process, allowing for smoother phase transitions in mixed-phase clouds compared to the previous approach. The new parameterization yields a model state which gives reasonable agreement with observed quantities, allowing for calculations of aerosol effects on mixed-phase clouds involving a reduced number of tunable parameters. Furthermore, we find a significant sensitivity to perturbations in ice nuclei concentrations with the new parameterization, which leads to a reversal of the traditional cloud lifetime effect.

Improving Parameterization of Entrainment Rate for Shallow Convection with Aircraft Measurements and Large-Eddy Simulation

DOE PAGES

Lu, Chunsong; Liu, Yangang; Zhang, Guang J.; ...

2016-02-01

This work examines the relationships of entrainment rate to vertical velocity, buoyancy, and turbulent dissipation rate by applying stepwise principal component regression to observational data from shallow cumulus clouds collected during the Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site near Lamont, Oklahoma. The cumulus clouds during the RACORO campaign simulated using a large eddy simulation (LES) model are also examined with the same approach. The analysis shows that a combination of multiple variables can better represent entrainment ratemore » in both the observations and LES than any single-variable fitting. Three commonly used parameterizations are also tested on the individual cloud scale. A new parameterization is therefore presented that relates entrainment rate to vertical velocity, buoyancy and dissipation rate; the effects of treating clouds as ensembles and humid shells surrounding cumulus clouds on the new parameterization are discussed. Physical mechanisms underlying the relationships of entrainment rate to vertical velocity, buoyancy and dissipation rate are also explored.« less

Evaluating Cloud Initialization in a Convection-permit NWP Model

NASA Astrophysics Data System (ADS)

Li, Jia; Chen, Baode

2015-04-01

In general, to avoid "double counting precipitation" problem, in convection permit NWP models, it was a common practice to turn off convective parameterization. However, if there were not any cloud information in the initial conditions, the occurrence of precipitation could be delayed due to spin-up of cloud field or microphysical variables. In this study, we utilized the complex cloud analysis package from the Advanced Regional Prediction System (ARPS) to adjust the initial states of the model on water substance, such as cloud water, cloud ice, rain water, et al., that is, to initialize the microphysical variables (i.e., hydrometers), mainly based on radar reflectivity observations. Using the Advanced Research WRF (ARW) model, numerical experiments with/without cloud initialization and convective parameterization were carried out at grey-zone resolutions (i.e. 1, 3, and 9 km). The results from the experiments without convective parameterization indicate that model ignition with radar reflectivity can significantly reduce spin-up time and accurately simulate precipitation at the initial time. In addition, it helps to improve location and intensity of predicted precipitation. With grey-zone resolutions (i.e. 1, 3, and 9 km), using the cumulus convective parameterization scheme (without radar data) cannot produce realistic precipitation at the early time. The issues related to microphysical parametrization associated with cloud initialization were also discussed.

A comprehensive parameterization of heterogeneous ice nucleation of dust surrogate: laboratory study with hematite particles and its application to atmospheric models

NASA Astrophysics Data System (ADS)

Hiranuma, N.; Paukert, M.; Steinke, I.; Zhang, K.; Kulkarni, G.; Hoose, C.; Schnaiter, M.; Saathoff, H.; Möhler, O.

2014-12-01

A new heterogeneous ice nucleation parameterization that covers a wide temperature range (-36 to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is important to accurately simulate the ice nucleation processes in cirrus clouds. The ice nucleation active surface-site density (ns) of hematite particles, used as a proxy for atmospheric dust particles, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions. These conditions were achieved by continuously changing the temperature (T) and relative humidity with respect to ice (RHice) in the chamber. Our measurements showed several different pathways to nucleate ice depending on T and RHice conditions. For instance, almost T-independent freezing was observed at -60 °C < T < -50 °C, where RHice explicitly controlled ice nucleation efficiency, while both T and RHice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T lower than -60 °C revealed that higher RHice was necessary to maintain a constant ns, whereas T may have played a significant role in ice nucleation at T higher than -50 °C. We implemented the new hematite-derived ns parameterization, which agrees well with previous AIDA measurements of desert dust, into two conceptual cloud models to investigate their sensitivity to the new parameterization in comparison to existing ice nucleation schemes for simulating cirrus cloud properties. Our results show that the new AIDA-based parameterization leads to an order of magnitude higher ice crystal concentrations and to an inhibition of homogeneous nucleation in lower-temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have a stronger influence on cloud properties, such as cloud longevity and initiation, compared to previous parameterizations.

Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5)

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

Shi, Xiangjun; Liu, Xiaohong; Zhang, Kai

In order to improve the treatment of ice nucleation in a more realistic manner in the Community Atmosphere Model version 5.3 (CAM5.3), the effects of pre-existing ice crystals on ice nucleation in cirrus clouds are considered. In addition, by considering the in-cloud variability in ice saturation ratio, homogeneous nucleation takes place spatially only in a portion of the cirrus cloud rather than in the whole area of the cirrus cloud. Compared to observations, the ice number concentrations and the probability distributions of ice number concentration are both improved with the updated treatment. The pre-existing ice crystals significantly reduce ice numbermore » concentrations in cirrus clouds, especially at mid- to high latitudes in the upper troposphere (by a factor of ~10). Furthermore, the contribution of heterogeneous ice nucleation to cirrus ice crystal number increases considerably. Besides the default ice nucleation parameterization of Liu and Penner (2005, hereafter LP) in CAM5.3, two other ice nucleation parameterizations of Barahona and Nenes (2009, hereafter BN) and Kärcher et al. (2006, hereafter KL) are implemented in CAM5.3 for the comparison. In-cloud ice crystal number concentration, percentage contribution from heterogeneous ice nucleation to total ice crystal number, and pre-existing ice effects simulated by the three ice nucleation parameterizations have similar patterns in the simulations with present-day aerosol emissions. However, the change (present-day minus pre-industrial times) in global annual mean column ice number concentration from the KL parameterization (3.24 × 10 6 m -2) is less than that from the LP (8.46 × 10 6 m -2) and BN (5.62 × 10 6 m -2) parameterizations. As a result, the experiment using the KL parameterization predicts a much smaller anthropogenic aerosol long-wave indirect forcing (0.24 W m -2) than that using the LP (0.46 W m −2) and BN (0.39 W m -2) parameterizations.« less

Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5)

DOE PAGES

Shi, Xiangjun; Liu, Xiaohong; Zhang, Kai

2015-02-11

In order to improve the treatment of ice nucleation in a more realistic manner in the Community Atmosphere Model version 5.3 (CAM5.3), the effects of pre-existing ice crystals on ice nucleation in cirrus clouds are considered. In addition, by considering the in-cloud variability in ice saturation ratio, homogeneous nucleation takes place spatially only in a portion of the cirrus cloud rather than in the whole area of the cirrus cloud. Compared to observations, the ice number concentrations and the probability distributions of ice number concentration are both improved with the updated treatment. The pre-existing ice crystals significantly reduce ice numbermore » concentrations in cirrus clouds, especially at mid- to high latitudes in the upper troposphere (by a factor of ~10). Furthermore, the contribution of heterogeneous ice nucleation to cirrus ice crystal number increases considerably. Besides the default ice nucleation parameterization of Liu and Penner (2005, hereafter LP) in CAM5.3, two other ice nucleation parameterizations of Barahona and Nenes (2009, hereafter BN) and Kärcher et al. (2006, hereafter KL) are implemented in CAM5.3 for the comparison. In-cloud ice crystal number concentration, percentage contribution from heterogeneous ice nucleation to total ice crystal number, and pre-existing ice effects simulated by the three ice nucleation parameterizations have similar patterns in the simulations with present-day aerosol emissions. However, the change (present-day minus pre-industrial times) in global annual mean column ice number concentration from the KL parameterization (3.24 × 10 6 m -2) is less than that from the LP (8.46 × 10 6 m -2) and BN (5.62 × 10 6 m -2) parameterizations. As a result, the experiment using the KL parameterization predicts a much smaller anthropogenic aerosol long-wave indirect forcing (0.24 W m -2) than that using the LP (0.46 W m −2) and BN (0.39 W m -2) parameterizations.« less

Collaborative Research: Using ARM Observations to Evaluate GCM Cloud Statistics for Development of Stochastic Cloud-Radiation Parameterizations

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

Shen, Samuel S. P.

2013-09-01

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been an interdisciplinary collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen). The motivation and long-term goal underlying this work is the utilization of stochastic radiative transfer theory (Lane-Veron and Somerville, 2004; Lane et al., 2002) to develop a new class of parametric representations of cloud-radiation interactions and closely related processes for atmospheric models. The theoretical advantage of the stochastic approach is that it can accurately calculate the radiative heating rates through a broken cloud layer without requiring an exact description of the cloud geometry.« less

Exploring Stratocumulus Cloud-Top Entrainment Processes and Parameterizations by Using Doppler Cloud Radar Observations

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

Albrecht, Bruce; Fang, Ming; Ghate, Virendra

2016-02-01

Observations from an upward-pointing Doppler cloud radar are used to examine cloud-top entrainment processes and parameterizations in a non-precipitating continental stratocumulus cloud deck maintained by time varying surface buoyancy fluxes and cloud-top radiative cooling. Radar and ancillary observations were made at the Atmospheric Radiation Measurement (ARM)’s Southern Great Plains (SGP) site located near Lamont, Oklahoma of unbroken, non-precipitating stratocumulus clouds observed for a 14-hour period starting 0900 Central Standard Time on 25 March 2005. The vertical velocity variance and energy dissipation rate (EDR) terms in a parameterized turbulence kinetic energy (TKE) budget of the entrainment zone are estimated using themore » radar vertical velocity and the radar spectrum width observations from the upward-pointing millimeter cloud radar (MMCR) operating at the SGP site. Hourly averages of the vertical velocity variance term in the TKE entrainment formulation correlates strongly (r=0.72) to the dissipation rate term in the entrainment zone. However, the ratio of the variance term to the dissipation decreases at night due to decoupling of the boundary layer. When the night -time decoupling is accounted for, the correlation between the variance and the EDR term increases (r=0.92). To obtain bulk coefficients for the entrainment parameterizations derived from the TKE budget, independent estimate of entrainment were obtained from an inversion height budget using ARM SGP observations of the local time derivative and the horizontal advection of the cloud-top height. The large-scale vertical velocity at the inversion needed for this budget from EMWF reanalysis. This budget gives a mean entrainment rate for the observing period of 0.76±0.15 cm/s. This mean value is applied to the TKE budget parameterizations to obtain the bulk coefficients needed in these parameterizations. These bulk coefficients are compared with those from previous and are used to in the parameterizations to give hourly estimates of the entrainment rates using the radar derived vertical velocity variance and dissipation rates. Hourly entrainment rates were estimated from a convective velocity w* parameterization depends on the local surface buoyancy fluxes and the calculated radiative flux divergence, parameterization using a bulk coefficient obtained from the mean inversion height budget. The hourly rates from the cloud turbulence estimates and the w* parameterization, which is independent of the radar observations, are compared with the hourly we values from the budget. All show rough agreement with each other and capture the entrainment variability associated with substantial changes in the surface flux and radiative divergence at cloud top. Major uncertainties in the hourly estimates from the height budget and w* are discussed. The results indicate a strong potential for making entrainment rate estimates directly from the radar vertical velocity variance and the EDR measurements—a technique that has distinct advantages over other methods for estimating entrainment rates. Calculations based on the EDR alone can provide high temporal resolution (for averaging intervals as small as 10 minutes) of the entrainment processes and do not require an estimate of the boundary layer depth, which can be difficult to define when the boundary layer is decoupled.« less

Modeling Cloud Phase Fraction Based on In-situ Observations in Stratiform Clouds

NASA Astrophysics Data System (ADS)

Boudala, F. S.; Isaac, G. A.

2005-12-01

Mixed-phase clouds influence weather and climate in several ways. Due to the fact that they exhibit very different optical properties as compared to ice or liquid only clouds, they play an important role in the earth's radiation balance by modifying the optical properties of clouds. Precipitation development in clouds is also enhanced under mixed-phase conditions and these clouds may contain large supercooled drops that freeze quickly in contact with aircraft surfaces that may be a hazard to aviation. The existence of ice and liquid phase clouds together in the same environment is thermodynamically unstable, and thus they are expected to disappear quickly. However, several observations show that mixed-phase clouds are relatively stable in the natural environment and last for several hours. Although there have been some efforts being made in the past to study the microphysical properties of mixed-phase clouds, there are still a number of uncertainties in modeling these clouds particularly in large scale numerical models. In most models, very simple temperature dependent parameterizations of cloud phase fraction are being used to estimate the fraction of ice or liquid phase in a given mixed-phase cloud. In this talk, two different parameterizations of ice fraction using in-situ aircraft measurements of cloud microphysical properties collected in extratropical stratiform clouds during several field programs will be presented. One of the parameterizations has been tested using a single prognostic equation developed by Tremblay et al. (1996) for application in the Canadian regional weather prediction model. The addition of small ice particles significantly increased the vapor deposition rate when the natural atmosphere is assumed to be water saturated, and thus this enhanced the glaciation of simulated mixed-phase cloud via the Bergeron-Findeisen process without significantly affecting the other cloud microphysical processes such as riming and particle sedimentation rates. After the water vapor pressure in mixed-phase cloud was modified based on the Lord et al. (1984) scheme by weighting the saturation water vapor pressure with ice fraction, it was possible to simulate more stable mixed-phase cloud. It was also noted that the ice particle concentration (L>100 μm) in mixed-phase cloud is lower on average by a factor 3 and as a result the parameterization should be corrected for this effect. After accounting for this effect, the parameterized ice fraction agreed well with observed mean ice fraction.

On testing two major cumulus parameterization schemes using the CSU Regional Atmospheric Modeling System

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

Kao, C.Y.J.; Bossert, J.E.; Winterkamp, J.

1993-10-01

One of the objectives of the DOE ARM Program is to improve the parameterization of clouds in general circulation models (GCMs). The approach taken in this research is two fold. We first examine the behavior of cumulus parameterization schemes by comparing their performance against the results from explicit cloud simulations with state-of-the-art microphysics. This is conducted in a two-dimensional (2-D) configuration of an idealized convective system. We then apply the cumulus parameterization schemes to realistic three-dimensional (3-D) simulations over the western US for a case with an enormous amount of convection in an extended period of five days. In themore » 2-D idealized tests, cloud effects are parameterized in the ``parameterization cases`` with a coarse resolution, whereas each cloud is explicitly resolved by the ``microphysics cases`` with a much finer resolution. Thus, the capability of the parameterization schemes in reproducing the growth and life cycle of a convective system can then be evaluated. These 2-D tests will form the basis for further 3-D realistic simulations which have the model resolution equivalent to that of the next generation of GCMs. Two cumulus parameterizations are used in this research: the Arakawa-Schubert (A-S) scheme (Arakawa and Schubert, 1974) used in Kao and Ogura (1987) and the Kuo scheme (Kuo, 1974) used in Tremback (1990). The numerical model used in this research is the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University (CSU).« less

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

NASA Astrophysics Data System (ADS)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

NASA Technical Reports Server (NTRS)

DeBoer, G.; Bauer, S. E.; Toto, T.; Menon, Surabi; Vogelmann, A. M.

2013-01-01

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Dependence of marine stratocumulus reflectivities on liquid water paths

NASA Technical Reports Server (NTRS)

Coakley, James A., Jr.; Snider, Jack B.

1990-01-01

Simple parameterizations that relate cloud liquid water content to cloud reflectivity are often used in general circulation climate models to calculate the effect of clouds in the earth's energy budget. Such parameterizations have been developed by Stephens (1978) and by Slingo and Schrecker (1982) and others. Here researchers seek to verify the parametric relationship through the use of simultaneous observations of cloud liquid water content and cloud reflectivity. The column amount of cloud liquid was measured using a microwave radiometer on San Nicolas Island following techniques described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of Advanced Very High Resolution Radiometer (AVHRR) imagery data (Coakley and Beckner, 1988). They present the dependence of the observed reflectivity on the observed liquid water path. They also compare this empirical relationship with that proposed by Stephens (1978). Researchers found that by taking clouds to be isotropic reflectors, the observed reflectivities and observed column amounts of cloud liquid water are related in a manner that is consistent with simple parameterizations often used in general circulation climate models to determine the effect of clouds on the earth's radiation budget. Attempts to use the results of radiative transfer calculations to correct for the anisotropy of the AVHRR derived reflectivities resulted in a greater scatter of the points about the relationship expected between liquid water path and reflectivity. The anisotropy of the observed reflectivities proved to be small, much smaller than indicated by theory. To critically assess parameterizations, more simultaneous observations of cloud liquid water and cloud reflectivities and better calibration of the AVHRR sensors are needed.

Atmospheric numerical modeling resource enhancement and model convective parameterization/scale interaction studies

NASA Technical Reports Server (NTRS)

Cushman, Paula P.

1993-01-01

Research will be undertaken in this contract in the area of Modeling Resource and Facilities Enhancement to include computer, technical and educational support to NASA investigators to facilitate model implementation, execution and analysis of output; to provide facilities linking USRA and the NASA/EADS Computer System as well as resident work stations in ESAD; and to provide a centralized location for documentation, archival and dissemination of modeling information pertaining to NASA's program. Additional research will be undertaken in the area of Numerical Model Scale Interaction/Convective Parameterization Studies to include implementation of the comparison of cloud and rain systems and convective-scale processes between the model simulations and what was observed; and to incorporate the findings of these and related research findings in at least two refereed journal articles.

Statistical properties of the normalized ice particle size distribution

NASA Astrophysics Data System (ADS)

Delanoë, Julien; Protat, Alain; Testud, Jacques; Bouniol, Dominique; Heymsfield, A. J.; Bansemer, A.; Brown, P. R. A.; Forbes, R. M.

2005-05-01

Testud et al. (2001) have recently developed a formalism, known as the "normalized particle size distribution (PSD)", which consists in scaling the diameter and concentration axes in such a way that the normalized PSDs are independent of water content and mean volume-weighted diameter. In this paper we investigate the statistical properties of the normalized PSD for the particular case of ice clouds, which are known to play a crucial role in the Earth's radiation balance. To do so, an extensive database of airborne in situ microphysical measurements has been constructed. A remarkable stability in shape of the normalized PSD is obtained. The impact of using a single analytical shape to represent all PSDs in the database is estimated through an error analysis on the instrumental (radar reflectivity and attenuation) and cloud (ice water content, effective radius, terminal fall velocity of ice crystals, visible extinction) properties. This resulted in a roughly unbiased estimate of the instrumental and cloud parameters, with small standard deviations ranging from 5 to 12%. This error is found to be roughly independent of the temperature range. This stability in shape and its single analytical approximation implies that two parameters are now sufficient to describe any normalized PSD in ice clouds: the intercept parameter N*0 and the mean volume-weighted diameter Dm. Statistical relationships (parameterizations) between N*0 and Dm have then been evaluated in order to reduce again the number of unknowns. It has been shown that a parameterization of N*0 and Dm by temperature could not be envisaged to retrieve the cloud parameters. Nevertheless, Dm-T and mean maximum dimension diameter -T parameterizations have been derived and compared to the parameterization of Kristjánsson et al. (2000) currently used to characterize particle size in climate models. The new parameterization generally produces larger particle sizes at any temperature than the Kristjánsson et al. (2000) parameterization. These new parameterizations are believed to better represent particle size at global scale, owing to a better representativity of the in situ microphysical database used to derive it. We then evaluated the potential of a direct N*0-Dm relationship. While the model parameterized by temperature produces strong errors on the cloud parameters, the N*0-Dm model parameterized by radar reflectivity produces accurate cloud parameters (less than 3% bias and 16% standard deviation). This result implies that the cloud parameters can be estimated from the estimate of only one parameter of the normalized PSD (N*0 or Dm) and a radar reflectivity measurement.

COLLABORATIVE RESEARCH:USING ARM OBSERVATIONS & ADVANCED STATISTICAL TECHNIQUES TO EVALUATE CAM3 CLOUDS FOR DEVELOPMENT OF STOCHASTIC CLOUD-RADIATION

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

Somerville, Richard

2013-08-22

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).« less

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

NASA Astrophysics Data System (ADS)

Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.

2012-12-01

Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.

Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

NASA Astrophysics Data System (ADS)

Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.

2013-12-01

Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.

Parameterization of Cloud Optical Properties for a Mixture of Ice Particles for use in Atmospheric Models

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lee, Kyu-Tae; Yang, Ping; Lau, William K. M. (Technical Monitor)

2002-01-01

Based on the single-scattering optical properties that are pre-computed using an improve geometric optics method, the bulk mass absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the mean effective particle size of a mixture of ice habits. The parameterization has been applied to compute fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. Compared to the parameterization for a single habit of hexagonal column, the solar heating of clouds computed with the parameterization for a mixture of habits is smaller due to a smaller cosingle-scattering albedo. Whereas the net downward fluxes at the TOA and surface are larger due to a larger asymmetry factor. The maximum difference in the cloud heating rate is approx. 0.2 C per day, which occurs in clouds with an optical thickness greater than 3 and the solar zenith angle less than 45 degrees. Flux difference is less than 10 W per square meters for the optical thickness ranging from 0.6 to 10 and the entire range of the solar zenith angle. The maximum flux difference is approximately 3%, which occurs around an optical thickness of 1 and at high solar zenith angles.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

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

Zheng, X.; Klein, S. A.; Ma, H. -Y.

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less

A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

DOE PAGES

Zheng, X.; Klein, S. A.; Ma, H. -Y.; ...

2017-08-24

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less

Improving Convection and Cloud Parameterization Using ARM Observations and NCAR Community Atmosphere Model CAM5

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

Zhang, Guang J.

2016-11-07

The fundamental scientific objectives of our research are to use ARM observations and the NCAR CAM5 to understand the large-scale control on convection, and to develop improved convection and cloud parameterizations for use in GCMs.

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

NASA Astrophysics Data System (ADS)

Xie, Xin

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

A~comprehensive parameterization of heterogeneous ice nucleation of dust surrogate: laboratory study with hematite particles and its application to atmospheric models

NASA Astrophysics Data System (ADS)

Hiranuma, N.; Paukert, M.; Steinke, I.; Zhang, K.; Kulkarni, G.; Hoose, C.; Schnaiter, M.; Saathoff, H.; Möhler, O.

2014-06-01

A new heterogeneous ice nucleation parameterization that covers a~wide temperature range (-36 to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is critical in order to accurately simulate the ice nucleation processes in cirrus clouds. The surface-scaled ice nucleation efficiencies of hematite particles, inferred by ns, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions that were realized by continuously changing temperature (T) and relative humidity with respect to ice (RHice) in the chamber. Our measurements showed several different pathways to nucleate ice depending on T and RHice conditions. For instance, almost T-independent freezing was observed at -60 °C < T < -50 °C, where RHice explicitly controlled ice nucleation efficiency, while both T and RHice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T colder than -60 °C revealed that higher RHice was necessary to maintain constant ns, whereas T may have played a significant role in ice nucleation at T warmer than -50 °C. We implemented new ns parameterizations into two cloud models to investigate its sensitivity and compare with the existing ice nucleation schemes towards simulating cirrus cloud properties. Our results show that the new AIDA-based parameterizations lead to an order of magnitude higher ice crystal concentrations and inhibition of homogeneous nucleation in colder temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have stronger influence on cloud properties such as cloud longevity and initiation when compared to previous parameterizations.

A Comprehensive Parameterization of Heterogeneous Ice Nucleation of Dust Surrogate: Laboratory Study with Hematite Particles and Its Application to Atmospheric Models

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

Hiranuma, Naruki; Paukert, Marco; Steinke, Isabelle

2014-12-10

A new heterogeneous ice nucleation parameterization that covers a wide temperature range (-36 °C to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is critical in order to accurately simulate the ice nucleation processes in cirrus clouds. The surface-scaled ice nucleation efficiencies of hematite particles, inferred by n s, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions that were realized by continuously changing temperature (T) and relative humidity with respect to ice (RH ice) in the chamber. Our measurementsmore » showed several different pathways to nucleate ice depending on T and RH ice conditions. For instance, almost independent freezing was observed at -60 °C < T < -50 °C, where RH ice explicitly controlled ice nucleation efficiency, while both T and RH ice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T colder than -60 °C revealed that higher RHice was necessary to maintain constant n s, whereas T may have played a significant role in ice nucleation at T warmer than -50 °C. We implemented new n s parameterizations into two cloud models to investigate its sensitivity and compare with the existing ice nucleation schemes towards simulating cirrus cloud properties. Our results show that the new AIDA-based parameterizations lead to an order of magnitude higher ice crystal concentrations and inhibition of homogeneous nucleation in colder temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have stronger influence on cloud properties such as cloud longevity and initiation when compared to previous parameterizations.« less

GEWEX Cloud Systems Study (GCSS)

NASA Technical Reports Server (NTRS)

Moncrieff, Mitch

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. I - Parameterization of radiance fields

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Liou, Kuo-Nan; Takano, Yoshihide

1993-01-01

The impact of using phase functions for spherical droplets and hexagonal ice crystals to analyze radiances from cirrus is examined. Adding-doubling radiative transfer calculations are employed to compute radiances for different cloud thicknesses and heights over various backgrounds. These radiances are used to develop parameterizations of top-of-the-atmosphere visible reflectance and IR emittance using tables of reflectances as a function of cloud optical depth, viewing and illumination angles, and microphysics. This parameterization, which includes Rayleigh scattering, ozone absorption, variable cloud height, and an anisotropic surface reflectance, reproduces the computed top-of-the-atmosphere reflectances with an accruacy of +/- 6 percent for four microphysical models: 10-micron water droplet, small symmetric crystal, cirrostratus, and cirrus uncinus. The accuracy is twice that of previous models.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Parameterization of Shortwave Cloud Optical Properties for a Mixture of Ice Particle Habits for use in Atmospheric Models

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lee, Kyu-Tae; Yang, Ping; Lau, William K. M. (Technical Monitor)

2002-01-01

Based on the single-scattering optical properties pre-computed with an improved geometric optics method, the bulk absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the effective particle size of a mixture of ice habits, the ice water amount, and spectral band. The parameterization has been applied to computing fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. It is found that flux calculations are not overly sensitive to the assumed particle habits if the definition of the effective particle size is consistent with the particle habits that the parameterization is based. Otherwise, the error in the flux calculations could reach a magnitude unacceptable for climate studies. Different from many previous studies, the parameterization requires only an effective particle size representing all ice habits in a cloud layer, but not the effective size of individual ice habits.

Structure and covariance of cloud and rain water in marine stratocumulus

NASA Astrophysics Data System (ADS)

Witte, Mikael; Morrison, Hugh; Gettelman, Andrew

2017-04-01

Many state of the art cloud microphysics parameterizations in large-scale models use assumed probability density functions (pdfs) to represent subgrid scale variability of relevant resolved scale variables such as vertical velocity and cloud liquid water content (LWC). Integration over the assumed pdfs of small scale variability results in physically consistent prediction of nonlinear microphysical process rates and obviates the need to apply arbitrary tuning parameters to the calculated rates. In such parameterizations, the covariance of cloud and rain LWC is an important quantity for parameterizing the accretion process by which rain drops grow via collection of cloud droplets. This covariance has been diagnosed by other workers from a variety of observational and model datasets (Boutle et al., 2013; Larson and Griffin, 2013; Lebsock et al., 2013), but there is poor agreement in findings across the studies. Two key assumptions that may explain some of the discrepancies among past studies are 1) LWC (both cloud and rain) distributions are statistically stationary and 2) spatial structure may be neglected. Given the highly intermittent nature of precipitation and the fact that cloud LWC has been found to be poorly represented by stationary pdfs (e.g. Marshak et al., 1997), neither of the aforementioned assumptions are valid. Therefore covariance must be evaluated as a function of spatial scale without the assumption of stationary statistics (i.e. variability cannot be expressed as a fractional standard deviation, which necessitates well-defined first and second moments of the LWC distribution). The present study presents multifractal analyses of both rain and cloud LWC using aircraft data from the VOCALS-REx field campaign to illustrate the importance of spatial structure in microphysical parameterizations and extends the results of Boutle et al. (2013) to provide a parameterization of rain-cloud water covariance as a function of spatial scale without the assumption of statistical stationarity.

Sensitivity of liquid clouds to homogenous freezing parameterizations.

PubMed

Herbert, Ross J; Murray, Benjamin J; Dobbie, Steven J; Koop, Thomas

2015-03-16

Water droplets in some clouds can supercool to temperatures where homogeneous ice nucleation becomes the dominant freezing mechanism. In many cloud resolving and mesoscale models, it is assumed that homogeneous ice nucleation in water droplets only occurs below some threshold temperature typically set at -40°C. However, laboratory measurements show that there is a finite rate of nucleation at warmer temperatures. In this study we use a parcel model with detailed microphysics to show that cloud properties can be sensitive to homogeneous ice nucleation as warm as -30°C. Thus, homogeneous ice nucleation may be more important for cloud development, precipitation rates, and key cloud radiative parameters than is often assumed. Furthermore, we show that cloud development is particularly sensitive to the temperature dependence of the nucleation rate. In order to better constrain the parameterization of homogeneous ice nucleation laboratory measurements are needed at both high (>-35°C) and low (<-38°C) temperatures. Homogeneous freezing may be significant as warm as -30°CHomogeneous freezing should not be represented by a threshold approximationThere is a need for an improved parameterization of homogeneous ice nucleation.

Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Khatri, P.; Iwabuchi, H.; Saito, M.

2017-12-01

High-level cirrus clouds, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

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

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

Wang, Zhien

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

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

NASA Astrophysics Data System (ADS)

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen; Ovchinnikov, Mikhail

2011-01-01

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling multispecies processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense. Existing lower and upper bounds on linear correlation coefficients are too loose to serve directly as a method to predict subgrid correlations. Therefore, this paper proposes an alternative method that begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are populated here using a "cSigma" parameterization that we introduce based on the aforementioned bounds on correlations. The method has three advantages: (1) the computational expense is tolerable; (2) the correlations are, by construction, guaranteed to be consistent with each other; and (3) the methodology is fairly general and hence may be applicable to other problems. The method is tested noninteractively using simulations of three Arctic mixed-phase cloud cases from two field experiments: the Indirect and Semi-Direct Aerosol Campaign and the Mixed-Phase Arctic Cloud Experiment. Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

“Using Statistical Comparisons between SPartICus Cirrus Microphysical Measurements, Detailed Cloud Models, and GCM Cloud Parameterizations to Understand Physical Processes Controlling Cirrus Properties and to Improve the Cloud Parameterizations”

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

Woods, Sarah

2015-12-01

The dual objectives of this project were improving our basic understanding of processes that control cirrus microphysical properties and improvement of the representation of these processes in the parameterizations. A major effort in the proposed research was to integrate, calibrate, and better understand the uncertainties in all of these measurements.

Using Field and Satellite Measurements to Improve Snow and Riming Processes in Cloud Resolving Models

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Molthan, Andrew L.

2013-01-01

The representation of clouds in climate and weather models is a driver in forecast uncertainty. Cloud microphysics parameterizations are challenged by having to represent a diverse range of ice species. Key characteristics of predicted ice species include habit and fall speed, and complex interactions that result from mixed-phased processes like riming. Our proposed activity leverages Global Precipitation Measurement (GPM) Mission ground validation studies to improve parameterizations

Coordinated Parameterization Development and Large-Eddy Simulation for Marine and Arctic Cloud-Topped Boundary Layers

NASA Technical Reports Server (NTRS)

Bretherton, Christopher S.

2002-01-01

The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

NASA Astrophysics Data System (ADS)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

A statistical comparison of cirrus particle size distributions measured using the 2-D stereo probe during the TC4, SPARTICUS, and MACPEX flight campaigns with historical cirrus datasets

NASA Astrophysics Data System (ADS)

Schwartz, M. Christian

2017-08-01

This paper addresses two straightforward questions. First, how similar are the statistics of cirrus particle size distribution (PSD) datasets collected using the Two-Dimensional Stereo (2D-S) probe to cirrus PSD datasets collected using older Particle Measuring Systems (PMS) 2-D Cloud (2DC) and 2-D Precipitation (2DP) probes? Second, how similar are the datasets when shatter-correcting post-processing is applied to the 2DC datasets? To answer these questions, a database of measured and parameterized cirrus PSDs - constructed from measurements taken during the Small Particles in Cirrus (SPARTICUS); Mid-latitude Airborne Cirrus Properties Experiment (MACPEX); and Tropical Composition, Cloud, and Climate Coupling (TC4) flight campaigns - is used.Bulk cloud quantities are computed from the 2D-S database in three ways: first, directly from the 2D-S data; second, by applying the 2D-S data to ice PSD parameterizations developed using sets of cirrus measurements collected using the older PMS probes; and third, by applying the 2D-S data to a similar parameterization developed using the 2D-S data themselves. This is done so that measurements of the same cloud volumes by parameterized versions of the 2DC and 2D-S can be compared with one another. It is thereby seen - given the same cloud field and given the same assumptions concerning ice crystal cross-sectional area, density, and radar cross section - that the parameterized 2D-S and the parameterized 2DC predict similar distributions of inferred shortwave extinction coefficient, ice water content, and 94 GHz radar reflectivity. However, the parameterization of the 2DC based on uncorrected data predicts a statistically significantly higher number of total ice crystals and a larger ratio of small ice crystals to large ice crystals than does the parameterized 2D-S. The 2DC parameterization based on shatter-corrected data also predicts statistically different numbers of ice crystals than does the parameterized 2D-S, but the comparison between the two is nevertheless more favorable. It is concluded that the older datasets continue to be useful for scientific purposes, with certain caveats, and that continuing field investigations of cirrus with more modern probes is desirable.

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

NASA Astrophysics Data System (ADS)

Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.

2017-12-01

Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.

Parameterized Radiative Convective Equilibrium Across a Range of Domains: A Unifying Tool for General Circulation Models and High Resolution Models

NASA Astrophysics Data System (ADS)

Silvers, L. G.; Stevens, B. B.; Mauritsen, T.; Marco, G. A.

2015-12-01

The characteristics of clouds in General Circulation Models (GCMs) need to be constrained in a consistent manner with theory, observations, and high resolution models (HRMs). One way forward is to base improvements of parameterizations on high resolution studies which resolve more of the important dynamical motions and allow for less parameterizations. This is difficult because of the numerous differences between GCMs and HRMs, both technical and theoretical. Century long simulations at resolutions of 20-250 km on a global domain are typical of GCMs while HRMs often simulate hours at resolutions of 0.1km-5km on domains the size of a single GCM grid cell. The recently developed mode ICON provides a flexible framework which allows many of these difficulties to be overcome. This study uses the ICON model to compute SST perturbation simulations on multiple domains in a state of Radiative Convective Equilibrium (RCE) with parameterized convection. The domains used range from roughly the size of Texas to nearly half of Earth's surface area. All simulations use a doubly periodic domain with an effective distance between cell centers of 13 km and are integrated to a state of statistical stationarity. The primary analysis examines the mean characteristics of the cloud related fields and the feedback parameter of the simulations. It is shown that the simulated atmosphere of a GCM in RCE is sufficiently similar across a range of domain sizes to justify the use of RCE to study both a GCM and a HRM on the same domain with the goal of improved constraints on the parameterized clouds. The simulated atmospheres are comparable to what could be expected at midday in a typical region of Earth's tropics under calm conditions. In particular, the differences between the domains are smaller than differences which result from choosing different physics schemes. Significant convective organization is present on all domain sizes with a relatively high subsidence fraction. Notwithstanding the overall qualitative similarities of the simulations, quantitative differences lead to a surprisingly large sensitivity of the feedback parameter. This range of the feedback parameter is more than a factor of two and is similar to the range of feedbacks which were obtained by the CMIP5 models.

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

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

Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less

Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

NASA Technical Reports Server (NTRS)

Lee,Wan-Ho; Iacobellis, Sam F.; Somerville, Richard C. J.

1997-01-01

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

Importance of Physico-Chemical Properties of Aerosols in the Formation of Arctic Ice Clouds

NASA Astrophysics Data System (ADS)

Keita, S. A.; Girard, E.

2014-12-01

Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation are poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TIC-1 are composed by non-precipitating very small (radar-unseen) ice crystals whereas TIC-2 are detected by both sensors and are characterized by a low concentration of large precipitating ice crystals. It is hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibit the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a smaller concentration of larger ice crystals. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation have been developed to reflect the various physical and chemical properties of aerosols. These parameterizations are derived from laboratory studies on aerosols of different chemical compositions. The parameterizations are also developed according to two main approaches: stochastic (that nucleation is a probabilistic process, which is time dependent) and singular (that nucleation occurs at fixed conditions of temperature and humidity and time-independent). This research aims to better understand the formation process of TICs using a newly-developed ice nucleation parameterizations. For this purpose, we implement some parameterizations (2 approaches) into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Arctic Cloud (ISDAC) in Alaska. We use both approaches but special attention is focused on the new parameterizations of the singular approach. Simulation results of the TICs-2 observed on April 15th and 25th (polluted or acidic cases) and TICs-1 observed on April 5th (non-polluted cases) will be presented.

On the usage of classical nucleation theory in predicting the impact of bacteria on weather and climate

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Woetmann Nielsen, Niels; Havskov Sørensen, Jens; Finster, Kai; Bay Gosewinkel Karlson, Ulrich; Šantl-Temkiv, Tina; Smith Korsholm, Ulrik

2014-05-01

Bacteria, e.g. Pseudomonas syringae, have previously been found efficient in nucleating ice heterogeneously at temperatures close to -2°C in laboratory tests. Therefore, ice nucleation active (INA) bacteria may be involved in the formation of precipitation in mixed phase clouds, and could potentially influence weather and climate. Investigations into the impact of INA bacteria on climate have shown that emissions were too low to significantly impact the climate (Hoose et al., 2010). The goal of this study is to clarify the reason for finding the marginal impact on climate when INA bacteria were considered, by investigating the usability of ice nucleation rate parameterization based on classical nucleation theory (CNT). For this purpose, two parameterizations of heterogeneous ice nucleation were compared. Both parameterizations were implemented and tested in a 1-d version of the operational weather model (HIRLAM) (Lynch et al., 2000; Unden et al., 2002) in two different meteorological cases. The first parameterization is based on CNT and denoted CH08 (Chen et al., 2008). This parameterization is a function of temperature and the size of the IN. The second parameterization, denoted HAR13, was derived from nucleation measurements of SnomaxTM (Hartmann et al., 2013). It is a function of temperature and the number of protein complexes on the outer membranes of the cell. The fraction of cloud droplets containing each type of IN as percentage in the cloud droplets population were used and the sensitivity of cloud ice production in each parameterization was compared. In this study, HAR13 produces more cloud ice and precipitation than CH08 when the bacteria fraction increases. In CH08, the increase of the bacteria fraction leads to decreasing the cloud ice mixing ratio. The ice production using HAR13 was found to be more sensitive to the change of the bacterial fraction than CH08 which did not show a similar sensitivity. As a result, this may explain the marginal impact of IN bacteria in climate models when CH08 was used. The number of cell fragments containing proteins appears to be a more important parameter to consider than the size of the cell when parameterizing the heterogeneous freezing of bacteria.

Trade-Wind Cloudiness and Climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1997-01-01

Closed Mesoscale Cellular Convection (MCC) consists of mesoscale cloud patches separated by narrow clear regions. Strong radiative cooling occurs at the cloud top. A dry two-dimensional Bousinesq model is used to study the effects of cloud-top cooling on convection. Wide updrafts and narrow downdrafts are used to indicate the asymmetric circulations associated with the mesoscale cloud patches. Based on the numerical results, a conceptual model was constructed to suggest a mechanism for the formation of closed MCC over cool ocean surfaces. A new method to estimate the radioative and evaporative cooling in the entrainment layer of a stratocumulus-topped boundary layer has been developed. The method was applied to a set of Large-Eddy Simulation (LES) results and to a set of tethered-balloon data obtained during FIRE. We developed a statocumulus-capped marine mixed layer model which includes a parameterization of drizzle based on the use of a predicted Cloud Condensation Nuclei (CCN) number concentration. We have developed, implemented, and tested a very elaborate new stratiform cloudiness parameterization for use in GCMs. Finally, we have developed a new, mechanistic parameterization of the effects of cloud-top cooling on the entrainment rate.

Observational Study and Parameterization of Aerosol-fog Interactions

NASA Astrophysics Data System (ADS)

Duan, J.; Guo, X.; Liu, Y.; Fang, C.; Su, Z.; Chen, Y.

2014-12-01

Studies have shown that human activities such as increased aerosols affect fog occurrence and properties significantly, and accurate numerical fog forecasting depends on, to a large extent, parameterization of fog microphysics and aerosol-fog interactions. Furthermore, fogs can be considered as clouds near the ground, and enjoy an advantage of permitting comprehensive long-term in-situ measurements that clouds do not. Knowledge learned from studying aerosol-fog interactions will provide useful insights into aerosol-cloud interactions. To serve the twofold objectives of understanding and improving parameterizations of aerosol-fog interactions and aerosol-cloud interactions, this study examines the data collected from fogs, with a focus but not limited to the data collected in Beijing, China. Data examined include aerosol particle size distributions measured by a Passive Cavity Aerosol Spectrometer Probe (PCASP-100X), fog droplet size distributions measured by a Fog Monitor (FM-120), Cloud Condensation Nuclei (CCN), liquid water path measured by radiometers and visibility sensors, along with meteorological variables measured by a Tethered Balloon Sounding System (XLS-Ⅱ) and Automatic Weather Station (AWS). The results will be compared with low-level clouds for similarities and differences between fogs and clouds.

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

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

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen

2011-08-16

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense.Existing lower and upper bounds (inequalities) on linear correlation coefficients provide useful guidance, but these bounds are too loose to serve directly as a method to predict subgrid correlations. Therefore,more » this paper proposes an alternative method that is based on a blend of theory and empiricism. The method begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are parameterized here using a cosine row-wise formula that is inspired by the aforementioned bounds on correlations. The method has three advantages: 1) the computational expense is tolerable; 2) the correlations are, by construction, guaranteed to be consistent with each other; and 3) the methodology is fairly general and hence may be applicable to other problems. The method is tested non-interactively using simulations of three Arctic mixed-phase cloud cases from two different field experiments: the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE). Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.« less

Parameterization Interactions in Global Aquaplanet Simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Suselj, Kay; Teixeira, João.

2018-02-01

Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

An Eddy-Diffusivity Mass-flux (EDMF) closure for the unified representation of cloud and convective processes

NASA Astrophysics Data System (ADS)

Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G.

2014-12-01

Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of results verifies the capacity of this closure to realistically represent different cloud and convective processes. Implementation of the closure in an idealized GCM allows us to study cloud feedbacks to climate change and to study the interactions between clouds, convections, and the large-scale circulation.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.

2005-01-01

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA-40 and ERA Interim) against CERES Tropical Deep Convective Cloud Object Observations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2008-01-01

This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.

The "Grey Zone" cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

NASA Astrophysics Data System (ADS)

Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel

2017-03-01

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity.

Observed reflectivities and liquid water content for marine stratocumulus

NASA Technical Reports Server (NTRS)

Coakley, J. A., Jr.; Snider, J. B.

1989-01-01

Simultaneous observations of cloud liquid water content and cloud reflectivity are used to verify their parametric relationship in a manner consistent with simple parameterizations often used in general-circulation climate models. The column amount of cloud liquid water was measured with a microwave radiometer on San Nicolas Island as described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of AVHRR imagery data as per Coakley and Baldwin (1984) and Coakley and Beckner (1988). The dependence of the observed reflectivity on the observed liquid water is discussed, and this empirical relationship is compared with the parameterization proposed by Stephens (1978).

FIRE Science Results 1989

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

An improved ice cloud formation parameterization in the EMAC model

NASA Astrophysics Data System (ADS)

Bacer, Sara; Pozzer, Andrea; Karydis, Vlassis; Tsimpidi, Alexandra; Tost, Holger; Sullivan, Sylvia; Nenes, Athanasios; Barahona, Donifan; Lelieveld, Jos

2017-04-01

Cirrus clouds cover about 30% of the Earth's surface and are an important modulator of the radiative energy budget of the atmosphere. Despite their importance in the global climate system, there are still large uncertainties in understanding the microphysical properties and interactions with aerosols. Ice crystal formation is quite complex and a variety of mechanisms exists for ice nucleation, depending on aerosol characteristics and environmental conditions. Ice crystals can be formed via homogeneous nucleation or heterogeneous nucleation of ice-nucleating particles in different ways (contact, immersion, condensation, deposition). We have implemented the computationally efficient cirrus cloud formation parameterization by Barahona and Nenes (2009) into the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model in order to improve the representation of ice clouds and aerosol-cloud interactions. The parameterization computes the ice crystal number concentration from precursor aerosols and ice-nucleating particles accounting for the competition between homogeneous and heterogeneous nucleation and among different freezing modes. Our work shows the differences and the improvements obtained after the implementation with respect to the previous version of EMAC.

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

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

Stephen J. Vavrus

2008-11-15

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

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.

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

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

Berg, L. K.; Shrivastava, M.; Easter, R. C.

A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convectivemore » cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

DOE PAGES

Berg, L. K.; Shrivastava, M.; Easter, R. C.; ...

2015-02-24

A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convectivemore » cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Fresh clouds: A parameterized updraft method for calculating cloud densities in one-dimensional models

NASA Astrophysics Data System (ADS)

Wong, Michael H.; Atreya, Sushil K.; Kuhn, William R.; Romani, Paul N.; Mihalka, Kristen M.

2015-01-01

Models of cloud condensation under thermodynamic equilibrium in planetary atmospheres are useful for several reasons. These equilibrium cloud condensation models (ECCMs) calculate the wet adiabatic lapse rate, determine saturation-limited mixing ratios of condensing species, calculate the stabilizing effect of latent heat release and molecular weight stratification, and locate cloud base levels. Many ECCMs trace their heritage to Lewis (Lewis, J.S. [1969]. Icarus 10, 365-378) and Weidenschilling and Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465-476). Calculation of atmospheric structure and gas mixing ratios are correct in these models. We resolve errors affecting the cloud density calculation in these models by first calculating a cloud density rate: the change in cloud density with updraft length scale. The updraft length scale parameterizes the strength of the cloud-forming updraft, and converts the cloud density rate from the ECCM into cloud density. The method is validated by comparison with terrestrial cloud data. Our parameterized updraft method gives a first-order prediction of cloud densities in a “fresh” cloud, where condensation is the dominant microphysical process. Older evolved clouds may be better approximated by another 1-D method, the diffusive-precipitative Ackerman and Marley (Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872-884) model, which represents a steady-state equilibrium between precipitation and condensation of vapor delivered by turbulent diffusion. We re-evaluate observed cloud densities in the Galileo Probe entry site (Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891-22910), and show that the upper and lower observed clouds at ∼0.5 and ∼3 bars are consistent with weak (cirrus-like) updrafts under conditions of saturated ammonia and water vapor, respectively. The densest observed cloud, near 1.3 bar, requires unexpectedly strong updraft conditions, or higher cloud density rates. The cloud density rate in this layer may be augmented by a composition with non-NH4SH components (possibly including adsorbed NH3).

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

NASA Astrophysics Data System (ADS)

Zhang, Lei; Dong, Xiquan; Kennedy, Aaron; Xi, Baike; Li, Zhanqing

2017-03-01

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%-20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

A physically-based approach of treating dust-water cloud interactions in climate models

NASA Astrophysics Data System (ADS)

Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-12-01

All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532

Towards a new parameterization of ice particles growth

NASA Astrophysics Data System (ADS)

Krakovska, Svitlana; Khotyayintsev, Volodymyr; Bardakov, Roman; Shpyg, Vitaliy

2017-04-01

Ice particles are the main component of polar clouds, unlike in warmer regions. That is why correct representation of ice particle formation and growth in NWP and other numerical atmospheric models is crucial for understanding of the whole chain of water transformation, including precipitation formation and its further deposition as snow in polar glaciers. Currently, parameterization of ice in atmospheric models is among the most difficult challenges. In the presented research, we present a renewed theoretical analysis of the evolution of mixed cloud or cold fog from the moment of ice nuclei activation until complete crystallization. The simplified model is proposed that includes both supercooled cloud droplets and initially uniform particles of ice, as well as water vapor. We obtain independent dimensionless input parameters of a cloud, and find main scenarios and stages of evolution of the microphysical state of the cloud. The characteristic times and particle sizes have been found, as well as the peculiarities of microphysical processes at each stage of evolution. In the future, the proposed original and physically grounded approximations may serve as a basis for a new scientifically substantiated and numerically efficient parameterizations of microphysical processes in mixed clouds for modern atmospheric models. The relevance of theoretical analysis is confirmed by numerical modeling for a wide range of combinations of possible conditions in the atmosphere, including cold polar regions. The main conclusion of the research is that until complete disappearance of cloud droplets, the growth of ice particles occurs at a practically constant humidity corresponding to the saturated humidity over water, regardless to all other parameters of a cloud. This process can be described by the one differential equation of the first order. Moreover, a dimensionless parameter has been proposed as a quantitative criterion of a transition from dominant depositional to intense collectional growth of ice particles; it could be used in models with bulk parameterization of cloud and precipitation formation processes.

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.

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Comments on “A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part I”

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

Zhang, Guang; Fan, Jiwen; Xu, Kuan-Man

2015-06-01

Arakawa and Wu (2013, hereafter referred to as AW13) recently developed a formal approach to a unified parameterization of atmospheric convection for high-resolution numerical models. The work is based on ideas formulated by Arakawa et al. (2011). It lays the foundation for a new parameterization pathway in the era of high-resolution numerical modeling of the atmosphere. The key parameter in this approach is convective cloud fraction. In conventional parameterization, it is assumed that <<1. This assumption is no longer valid when horizontal resolution of numerical models approaches a few to a few tens kilometers, since in such situations convective cloudmore » fraction can be comparable to unity. Therefore, they argue that the conventional approach to parameterizing convective transport must include a factor 1 - in order to unify the parameterization for the full range of model resolutions so that it is scale-aware and valid for large convective cloud fractions. While AW13’s approach provides important guidance for future convective parameterization development, in this note we intend to show that the conventional approach already has this scale awareness factor 1 - built in, although not recognized for the last forty years. Therefore, it should work well even in situations of large convective cloud fractions in high-resolution numerical models.« less

A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Pergaud, Julien; Masson, Valéry; Malardel, Sylvie; Couvreux, Fleur

2009-07-01

For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy DiffusivityMass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w *. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCSARM) and conserve a realistic evolution of stratocumulus (EUROCSFIRE).

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

The effect of different spectral shape parameterizations of cloud droplet size distribution on first and second aerosol indirect effects in NACR CAM5 and evaluation with satellite data

NASA Astrophysics Data System (ADS)

Wang, M.; Peng, Y.; Xie, X.; Liu, Y.

2017-12-01

Aerosol cloud interaction continues to constitute one of the most significant uncertainties for anthropogenic climate perturbations. The parameterization of cloud droplet size distribution and autoconversion process from large scale cloud to rain can influence the estimation of first and second aerosol indirect effects in global climate models. We design a series of experiments focusing on the microphysical cloud scheme of NCAR CAM5 (Community Atmospheric Model Version 5) in transient historical run with realistic sea surface temperature and sea ice. We investigate the effect of three empirical, two semi-empirical and one analytical expressions for droplet size distribution on cloud properties and explore the statistical relationships between aerosol optical thickness (AOT) and simulated cloud variables, including cloud top droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP). We also introduce the droplet spectral shape parameter into the autoconversion process to incorporate the effect of droplet size distribution on second aerosol indirect effect. Three satellite datasets (MODIS Terra/ MODIS Aqua/ AVHRR) are used to evaluate the simulated aerosol indirect effect from the model. Evident CDER decreasing with significant AOT increasing is found in the east coast of China to the North Pacific Ocean and the east coast of USA to the North Atlantic Ocean. Analytical and semi-empirical expressions for spectral shape parameterization show stronger first aerosol indirect effect but weaker second aerosol indirect effect than empirical expressions because of the narrower droplet size distribution.

Offline GCSS Intercomparison of Cloud-Radiation Interaction and Surface Fluxes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Johnson, D.; Krueger, S.; Zulauf, M.; Donner, L.; Seman, C.; Petch, J.; Gregory, J.

2004-01-01

Simulations of deep tropical clouds by both cloud-resolving models (CRMs) and single-column models (SCMs) in the GEWEX Cloud System Study (GCSS) Working Group 4 (WG4; Precipitating Convective Cloud Systems), Case 2 (19-27 December 1992, TOGA-COARE IFA) have produced large differences in the mean heating and moistening rates (-1 to -5 K and -2 to 2 grams per kilogram respectively). Since the large-scale advective temperature and moisture "forcing" are prescribed for this case, a closer examination of two of the remaining external types of "forcing", namely radiative heating and air/sea hear and moisture transfer, are warranted. This paper examines the current radiation and surface flux of parameterizations used in the cloud models participating in the GCSS WG4, be executing the models "offline" for one time step (12 s) for a prescribed atmospheric state, then examining the surface and radiation fluxes from each model. The dynamic, thermodynamic, and microphysical fluids are provided by the GCE-derived model output for Case 2 during a period of very active deep convection (westerly wind burst). The surface and radiation fluxes produced from the models are then divided into prescribed convective, stratiform, and clear regions in order to examine the role that clouds play in the flux parameterizations. The results suggest that the differences between the models are attributed more to the surface flux parameterizations than the radiation schemes.

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

NASA Astrophysics Data System (ADS)

Protat, A.; Delanoë, J.; May, P. T.; Haynes, J.; Jakob, C.; O'Connor, E.; Pope, M.; Wheeler, M. C.

2011-08-01

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Redistribution of ice nuclei between cloud and rain droplets: Parameterization and application to deep convective clouds

NASA Astrophysics Data System (ADS)

Paukert, M.; Hoose, C.; Simmel, M.

2017-03-01

In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. In contrast, the immersion freezing of larger drops—"rain"—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. Here we introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.

A Study of the Relationship Between Anthropogenic Sulfate and Cloud Drop Nucleation

NASA Technical Reports Server (NTRS)

Chuang, Catherine C.; Penner, Joyce E.

1994-01-01

The characteristics of the cloud drop size distribution near cloud base are initially determined by the aerosol particles that serve as CCN and by the local updraft velocity. Chemical reactions of the emitted gaseous sulfur compounds due to human activities will alter, through gas-to-particle conversion, the aerosol size distribution, total number, and its chemical composition. Recently, Boucher and Rodhe and Jones et.al have each developed parameterizations relating cloud drop concentration to sulfate mass or aerosol number concentration, respectively, and used them to develop estimates of the indirect forcing by anthropogenic sulfate aerosols. THese parameterizations made use of measure relationships in continental and maritime clouds. However, these relationships are inherently noisy, yielding more than a factor of 2 variation in cloud drop concentration for a given aerosol number (or for a given sulfate mass) concentration. The large spatial and temporal variabilities in the concentration, chemical characteristics, and size distribution of aerosols have made it difficult to develop such a parameterization from data. In this paper, our focus is to develop a means for relating the predicted anthropogenic sulfate mass to cloud drop number concentration over the range of expected conditions associated with continental and marine aerosol. We start with an assumed pre-existing particle size distribution and develop an approximation of the altered distribution after addition of anthropogenic sulfate. We thereby develop a conservative estimate of the possible change in cloud drop number concentration due to anthropogenic sulfate.

Cloud microphysics modification with an online coupled COSMO-MUSCAT regional model

NASA Astrophysics Data System (ADS)

Sudhakar, D.; Quaas, J.; Wolke, R.; Stoll, J.; Muehlbauer, A. D.; Tegen, I.

2015-12-01

Abstract: The quantification of clouds, aerosols, and aerosol-cloud interactions in models, continues to be a challenge (IPCC, 2013). In this scenario two-moment bulk microphysical scheme is used to understand the aerosol-cloud interactions in the regional model COSMO (Consortium for Small Scale Modeling). The two-moment scheme in COSMO has been especially designed to represent aerosol effects on the microphysics of mixed-phase clouds (Seifert et al., 2006). To improve the model predictability, the radiation scheme has been coupled with two-moment microphysical scheme. Further, the cloud microphysics parameterization has been modified via coupling COSMO with MUSCAT (MultiScale Chemistry Aerosol Transport model, Wolke et al., 2004). In this study, we will be discussing the initial result from the online-coupled COSMO-MUSCAT model system with modified two-moment parameterization scheme along with COSP (CFMIP Observational Simulator Package) satellite simulator. This online coupled model system aims to improve the sub-grid scale process in the regional weather prediction scenario. The constant aerosol concentration used in the Seifert and Beheng, (2006) parameterizations in COSMO model has been replaced by aerosol concentration derived from MUSCAT model. The cloud microphysical process from the modified two-moment scheme is compared with stand-alone COSMO model. To validate the robustness of the model simulation, the coupled model system is integrated with COSP satellite simulator (Muhlbauer et al., 2012). Further, the simulations are compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and ISCCP (International Satellite Cloud Climatology Project) satellite products.

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.

Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

NASA Technical Reports Server (NTRS)

Titlow, James; Baum, Bryan A.

1993-01-01

Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

There are two possible approaches for parameterizing sub-grid cloud dynamics in a coarser grid model. The most common is to use a fine scale model to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to parameterize these behaviors cloud state for the coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical mechanics. This approach avoids any requirement to resolve time-dependent processes in order to arrive at a suitable solution. The second approach is widely used elsewhere in the atmospheric sciences: for example the Planck function for blackbody radiation is derived this way, where no mention is made of the complexities of modeling a large ensemble of time-dependent radiation-dipole interactions in order to obtain the "grid-scale" spectrum of thermal emission by the blackbody as a whole. We find that this statistical approach may be equally suitable for modeling convective clouds. Specifically, we make the physical argument that the dissipation of buoyant energy in convective clouds is done through mixing across a cloud perimeter. From thermodynamic reasoning, one might then anticipate that vertically stacked isentropic surfaces are characterized by a power law dlnN/dlnP = -1, where N(P) is the number clouds of perimeter P. In a Giga-LES simulation of convective clouds within a 100 km square domain we find that such a power law does appear to characterize simulated cloud perimeters along isentropes, provided a sufficient cloudy sample. The suggestion is that it may be possible to parameterize certain important aspects of cloud state without appealing to computationally expensive dynamic simulations.

The effects of atmospheric cloud radiative forcing on climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1989-01-01

In order to isolate the effects of atmospheric cloud radiative forcing (ACRF) on climate, the general circulation of an ocean-covered earth called 'Seaworld' was simulated using the Colorado State University GCM. Most current climate models, however, do not include an interactive ocean. The key simplifications in 'Seaworld' are the fixed boundary temperature with no land points, the lack of mountains and the zonal uniformity of the boundary conditions. Two 90-day 'perpetual July' simulations were performed and analyzed the last sixty days of each. The first run included all the model's physical parameterizations, while the second omitted the effects of clouds in both the solar and terrestrial radiation parameterizations. Fixed and identical boundary temperatures were set for the two runs, and resulted in differences revealing the direct and indirect effects of the ACRF on the large-scale circulation and the parameterized hydrologic processes.

Testing cloud microphysics parameterizations in NCAR CAM5 with ISDAC and M-PACE observations

NASA Astrophysics Data System (ADS)

Liu, Xiaohong; Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Shi, Xiangjun; Wang, Zhien; Lin, Wuyin; Ghan, Steven J.; Earle, Michael; Liu, Peter S. K.; Zelenyuk, Alla

2011-01-01

Arctic clouds simulated by the National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 5 (CAM5) are evaluated with observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Indirect and Semi-Direct Aerosol Campaign (ISDAC) and Mixed-Phase Arctic Cloud Experiment (M-PACE), which were conducted at its North Slope of Alaska site in April 2008 and October 2004, respectively. Model forecasts for the Arctic spring and fall seasons performed under the Cloud-Associated Parameterizations Testbed framework generally reproduce the spatial distributions of cloud fraction for single-layer boundary-layer mixed-phase stratocumulus and multilayer or deep frontal clouds. However, for low-level stratocumulus, the model significantly underestimates the observed cloud liquid water content in both seasons. As a result, CAM5 significantly underestimates the surface downward longwave radiative fluxes by 20-40 W m-2. Introducing a new ice nucleation parameterization slightly improves the model performance for low-level mixed-phase clouds by increasing cloud liquid water content through the reduction of the conversion rate from cloud liquid to ice by the Wegener-Bergeron-Findeisen process. The CAM5 single-column model testing shows that changing the instantaneous freezing temperature of rain to form snow from -5°C to -40°C causes a large increase in modeled cloud liquid water content through the slowing down of cloud liquid and rain-related processes (e.g., autoconversion of cloud liquid to rain). The underestimation of aerosol concentrations in CAM5 in the Arctic also plays an important role in the low bias of cloud liquid water in the single-layer mixed-phase clouds. In addition, numerical issues related to the coupling of model physics and time stepping in CAM5 are responsible for the model biases and will be explored in future studies.

Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

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

Nenes, Athanasios

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less

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

NASA Technical Reports Server (NTRS)

Molthan, A. L.; Haynes, J. A.; Jedlovec, G. L.; Lapenta, W. M.

2009-01-01

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Integrating Cloud Processes in the Community Atmosphere Model, Version 5.

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

Park, S.; Bretherton, Christopher S.; Rasch, Philip J.

2014-09-15

This paper provides a description on the parameterizations of global cloud system in CAM5. Compared to the previous versions, CAM5 cloud parameterization has the following unique characteristics: (1) a transparent cloud macrophysical structure that has horizontally non-overlapped deep cumulus, shallow cumulus and stratus in each grid layer, each of which has own cloud fraction, mass and number concentrations of cloud liquid droplets and ice crystals, (2) stratus-radiation-turbulence interaction that allows CAM5 to simulate marine stratocumulus solely from grid-mean RH without relying on the stability-based empirical empty stratus, (3) prognostic treatment of the number concentrations of stratus liquid droplets and icemore » crystals with activated aerosols and detrained in-cumulus condensates as the main sources and evaporation-sedimentation-precipitation of stratus condensate as the main sinks, and (4) radiatively active cumulus. By imposing consistency between diagnosed stratus fraction and prognosed stratus condensate, CAM5 is free from empty or highly-dense stratus at the end of stratus macrophysics. CAM5 also prognoses mass and number concentrations of various aerosol species. Thanks to the aerosol activation and the parameterizations of the radiation and stratiform precipitation production as a function of the droplet size, CAM5 simulates various aerosol indirect effects associated with stratus as well as direct effects, i.e., aerosol controls both the radiative and hydrological budgets. Detailed analysis of various simulations revealed that CAM5 is much better than CAM3/4 in the global performance as well as the physical formulation. However, several problems were also identifed, which can be attributed to inappropriate regional tuning, inconsistency between various physics parameterizations, and incomplete model physics. Continuous efforts are going on to further improve CAM5.« less

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

New Approaches to Parameterizing Convection

NASA Technical Reports Server (NTRS)

Randall, David A.; Lappen, Cara-Lyn

1999-01-01

Many general circulation models (GCMs) currently use separate schemes for planetary boundary layer (PBL) processes, shallow and deep cumulus (Cu) convection, and stratiform clouds. The conventional distinctions. among these processes are somewhat arbitrary. For example, in the stratocumulus-to-cumulus transition region, stratocumulus clouds break up into a combination of shallow cumulus and broken stratocumulus. Shallow cumulus clouds may be considered to reside completely within the PBL, or they may be regarded as starting in the PBL but terminating above it. Deeper cumulus clouds often originate within the PBL with also can originate aloft. To the extent that our models separately parameterize physical processes which interact strongly on small space and time scales, the currently fashionable practice of modularization may be doing more harm than good.

Improving microphysics in a convective parameterization: possibilities and limitations

NASA Astrophysics Data System (ADS)

Labbouz, Laurent; Heikenfeld, Max; Stier, Philip; Morrison, Hugh; Milbrandt, Jason; Protat, Alain; Kipling, Zak

2017-04-01

The convective cloud field model (CCFM) is a convective parameterization implemented in the climate model ECHAM6.1-HAM2.2. It represents a population of clouds within each ECHAM-HAM model column, simulating up to 10 different convective cloud types with individual radius, vertical velocities and microphysical properties. Comparisons between CCFM and radar data at Darwin, Australia, show that in order to reproduce both the convective cloud top height distribution and the vertical velocity profile, the effect of aerodynamic drag on the rising parcel has to be considered, along with a reduced entrainment parameter. A new double-moment microphysics (the Predicted Particle Properties scheme, P3) has been implemented in the latest version of CCFM and is compared to the standard single-moment microphysics and the radar retrievals at Darwin. The microphysical process rates (autoconversion, accretion, deposition, freezing, …) and their response to changes in CDNC are investigated and compared to high resolution CRM WRF simulations over the Amazon region. The results shed light on the possibilities and limitations of microphysics improvements in the framework of CCFM and in convective parameterizations in general.

A Solar Radiation Parameterization for Atmospheric Studies. Volume 15

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Suarez, Max J. (Editor)

1999-01-01

The solar radiation parameterization (CLIRAD-SW) developed at the Goddard Climate and Radiation Branch for application to atmospheric models are described. It includes the absorption by water vapor, O3, O2, CO2, clouds, and aerosols and the scattering by clouds, aerosols, and gases. Depending upon the nature of absorption, different approaches are applied to different absorbers. In the ultraviolet and visible regions, the spectrum is divided into 8 bands, and single O3 absorption coefficient and Rayleigh scattering coefficient are used for each band. In the infrared, the spectrum is divided into 3 bands, and the k-distribution method is applied for water vapor absorption. The flux reduction due to O2 is derived from a simple function, while the flux reduction due to CO2 is derived from precomputed tables. Cloud single-scattering properties are parameterized, separately for liquid drops and ice, as functions of water amount and effective particle size. A maximum-random approximation is adopted for the overlapping of clouds at different heights. Fluxes are computed using the Delta-Eddington approximation.

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

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

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

2010-02-22

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

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Lee, Dongmin; Norris, Peter; Yuan, Tianle

2011-01-01

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Importance of Chemical Composition of Ice Nuclei on the Formation of Arctic Ice Clouds

NASA Astrophysics Data System (ADS)

Keita, Setigui Aboubacar; Girard, Eric

2016-09-01

Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation remain poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TICs-1 are composed by non-precipitating small (radar-unseen) ice crystals of less than 30 μm in diameter. The second type, TICs-2, are detected by radar and are characterized by a low concentration of large precipitating ice crystals ice crystals (>30 μm). To explain these differences, we hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibits the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a lower concentration of larger ice crystals. Water vapor available for deposition being the same, these crystals reach a larger size. Current weather and climate models cannot simulate these different types of ice clouds. This problem is partly due to the parameterizations implemented for ice nucleation. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation on IN of different chemical compositions have been developed. These parameterizations are based on two approaches: stochastic (that is nucleation is a probabilistic process, which is time dependent) and singular (that is nucleation occurs at fixed conditions of temperature and humidity and time-independent). The best approach remains unclear. This research aims to better understand the formation process of Arctic TICs using recently developed ice nucleation parameterizations. For this purpose, we have implemented these ice nucleation parameterizations into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska. Simulation results of the TICs-2 observed on April 15th and 25th (acidic cases) and TICs-1 observed on April 5th (non-acidic cases) are presented. Our results show that the stochastic approach based on the classical nucleation theory with the appropriate contact angle is better. Parameterizations of ice nucleation based on the singular approach tend to overestimate the ice crystal concentration in TICs-1 and TICs-2. The classical nucleation theory using the appropriate contact angle is the best approach to use to simulate the ice clouds investigated in this research.

The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team

NASA Astrophysics Data System (ADS)

Grosvenor, D. P.; Wood, R.

2012-12-01

As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB parameterization. The CAM5 model produces realistic near-coast cloud cover, but too little further west in the stratocumulus to cumulus regions. The implementation of CLUBB has vastly improved this situation with cloud cover that is very similar to that observed. CLUBB also improves the Nd field in CAM5 by producing realistic near-coast increases and by removing high Nd values associated with the detrainment of droplets by cumulus clouds. AM3 has a lack of stratocumulus cloud near the South American coast and has much lower droplet concentrations than observed. VOCALS measurements showed that sulfate mass loadings were generally too high in both base models, whereas CCN concentrations were too low. This suggests a problem with the mass distribution partitioning of sulfate that is being investigated. Diurnal and seasonal comparisons have been very illuminating. CLUBB produces very little diurnal variation in LWP, but large variations in precipitation rates. This is likely to point to problems that are now being addressed by the modeling part of the CPT team, creating an iterative workflow process between the model developers and the model testers, which should facilitate efficient parameterization improvement. We will report on the latest developments of this process.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Evaluation of WRF physical parameterizations against ARM/ASR Observations in the post-cold-frontal region to improve low-level clouds representation in CAM5

NASA Astrophysics Data System (ADS)

Lamraoui, F.; Booth, J. F.; Naud, C. M.

2017-12-01

The representation of subgrid-scale processes of low-level marine clouds located in the post-cold-frontal region poses a serious challenge for climate models. More precisely, the boundary layer parameterizations are predominantly designed for individual regimes that can evolve gradually over time and does not accommodate the cold front passage that can overly modify the boundary layer rapidly. Also, the microphysics schemes respond differently to the quick development of the boundary layer schemes, especially under unstable conditions. To improve the understanding of cloud physics in the post-cold frontal region, the present study focuses on exploring the relationship between cloud properties, the local processes and large-scale conditions. In order to address these questions, we explore the WRF sensitivity to the interaction between various combinations of the boundary layer and microphysics parameterizations, including the Community Atmospheric Model version 5 (CAM5) physical package in a perturbed physics ensemble. Then, we evaluate these simulations against ground-based ARM observations over the Azores. The WRF-based simulations demonstrate particular sensitivities of the marine cold front passage and the associated post-cold frontal clouds to the domain size, the resolution and the physical parameterizations. First, it is found that in multiple different case studies the model cannot generate the cold front passage when the domain size is larger than 3000 km2. Instead, the modeled cold front stalls, which shows the importance of properly capturing the synoptic scale conditions. The simulation reveals persistent delay in capturing the cold front passage and also an underestimated duration of the post-cold-frontal conditions. Analysis of the perturbed physics ensemble shows that changing the microphysics scheme leads to larger differences in the modeled clouds than changing the boundary layer scheme. The in-cloud heating tendencies are analyzed to explain this sensitivity.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Redistribution of ice nuclei between cloud and rain droplets: Parameterization and application to deep convective clouds: ICE NUCLEI IN RAIN DROPLETS

DOE PAGES

Paukert, M.; Hoose, C.; Simmel, M.

2017-02-21

In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation inmore » raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.« less

Redistribution of ice nuclei between cloud and rain droplets: Parameterization and application to deep convective clouds: ICE NUCLEI IN RAIN DROPLETS

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

Paukert, M.; Hoose, C.; Simmel, M.

In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation inmore » raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.« less

Physics Parameterization for Seasonal Prediction

DTIC Science & Technology

2012-09-30

comparison Project, a joint effort between the Year of Tropical Convection (YOTC) Program and the Global Energy and Water Cycle Experiment (GEWEX) Cloud...unified” representation of the water cycle in the model. One such area is the correspondence between diagnosed cloud cover and prognostic cloud

Investigating the Variability in Cumulus Cloud Number as a Function of Subdomain Size and Organization using large-domain LES

NASA Astrophysics Data System (ADS)

Neggers, R.

2017-12-01

Recent advances in supercomputing have introduced a "grey zone" in the representation of cumulus convection in general circulation models, in which this process is partially resolved. Cumulus parameterizations need to be made scale-aware and scale-adaptive to be able to conceptually and practically deal with this situation. A potential way forward are schemes formulated in terms of discretized Cloud Size Densities, or CSDs. Advantages include i) the introduction of scale-awareness at the foundation of the scheme, and ii) the possibility to apply size-filtering of parameterized convective transport and clouds. The CSD is a new variable that requires closure; this concerns its shape, its range, but also variability in cloud number that can appear due to i) subsampling effects and ii) organization in a cloud field. The goal of this study is to gain insight by means of sub-domain analyses of various large-domain LES realizations of cumulus cloud populations. For a series of three-dimensional snapshots, each with a different degree of organization, the cloud size distribution is calculated in all subdomains, for a range of subdomain sizes. The standard deviation of the number of clouds of a certain size is found to decrease with the subdomain size, following a powerlaw scaling corresponding to an inverse-linear dependence. Cloud number variability also increases with cloud size; this reflects that subsampling affects the largest clouds first, due to their typically larger neighbor spacing. Rewriting this dependence in terms of two dimensionless groups, by dividing by cloud number and cloud size respectively, yields a data collapse. Organization in the cloud field is found to act on top of this primary dependence, by enhancing the cloud number variability at the smaller sizes. This behavior reflects that small clouds start to "live" on top of larger structures such as cold pools, favoring or inhibiting their formation (as illustrated by the attached figure of cloud mask). Powerlaw scaling is still evident, but with a reduced exponent, suggesting that this behavior could be parameterized.

Sensitivity study of cloud parameterizations with relative dispersion in CAM5.1: impacts on aerosol indirect effects

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

Xie, Xiaoning; Zhang, He; Liu, Xiaodong

Aerosol-induced increase of relative dispersion of cloud droplet size distribution ε exerts a warming effect and partly offsets the cooling of aerosol indirect radiative forcing (AIF) associated with increased droplet concentration by increasing the cloud droplet effective radius ( R e) and enhancing the cloud-to-rain autoconversion rate (Au) (labeled aBut, the total dispersion effects on both R e and Au are not fully considered in most GCMs, especially in different versions of the Community Atmospheric Model (CAM). Furthermore, in order to accurately evaluate the dispersion effect on AIF, the new complete cloud parameterizations of R e and Au explicitly accountingmore » for ε are implemented into the CAM version 5.1 (CAM5.1), and a suite of sensitivity experiments is conducted with different representations of ε reported in the literature. It is shown that the shortwave cloud radiative forcing is much better simulated with the new cloud parameterizations as compared to the standard scheme in CAM5.1, whereas the influences on longwave cloud radiative forcing and surface precipitation are minimal. In addition, consideration of the dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, especially in the Northern Hemisphere. The corresponding AIF with the dispersion effect considered can also be reduced substantially by a range of 0.10 to 0.21 W m -2 at the global scale and by a much bigger margin of 0.25 to 0.39 W m -2 for the Northern Hemisphere in comparison with that of fixed relative dispersion, mainly dependent on the change of relative dispersion and droplet concentrations (Δε/ΔN).« less

Sensitivity study of cloud parameterizations with relative dispersion in CAM5.1: impacts on aerosol indirect effects

NASA Astrophysics Data System (ADS)

Xie, Xiaoning; Zhang, He; Liu, Xiaodong; Peng, Yiran; Liu, Yangang

2017-05-01

Aerosol-induced increase of relative dispersion of cloud droplet size distribution ɛ exerts a warming effect and partly offsets the cooling of aerosol indirect radiative forcing (AIF) associated with increased droplet concentration by increasing the cloud droplet effective radius (Re) and enhancing the cloud-to-rain autoconversion rate (Au) (labeled as the dispersion effect), which can help reconcile global climate models (GCMs) with the satellite observations. However, the total dispersion effects on both Re and Au are not fully considered in most GCMs, especially in different versions of the Community Atmospheric Model (CAM). In order to accurately evaluate the dispersion effect on AIF, the new complete cloud parameterizations of Re and Au explicitly accounting for ɛ are implemented into the CAM version 5.1 (CAM5.1), and a suite of sensitivity experiments is conducted with different representations of ɛ reported in the literature. It is shown that the shortwave cloud radiative forcing is much better simulated with the new cloud parameterizations as compared to the standard scheme in CAM5.1, whereas the influences on longwave cloud radiative forcing and surface precipitation are minimal. Additionally, consideration of the dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, especially in the Northern Hemisphere. The corresponding AIF with the dispersion effect considered can also be reduced substantially by a range of 0.10 to 0.21 W m-2 at the global scale and by a much bigger margin of 0.25 to 0.39 W m-2 for the Northern Hemisphere in comparison with that of fixed relative dispersion, mainly dependent on the change of relative dispersion and droplet concentrations (Δɛ/ΔNc).

Sensitivity study of cloud parameterizations with relative dispersion in CAM5.1: impacts on aerosol indirect effects

DOE PAGES

Xie, Xiaoning; Zhang, He; Liu, Xiaodong; ...

2017-05-12

Aerosol-induced increase of relative dispersion of cloud droplet size distribution ε exerts a warming effect and partly offsets the cooling of aerosol indirect radiative forcing (AIF) associated with increased droplet concentration by increasing the cloud droplet effective radius ( R e) and enhancing the cloud-to-rain autoconversion rate (Au) (labeled aBut, the total dispersion effects on both R e and Au are not fully considered in most GCMs, especially in different versions of the Community Atmospheric Model (CAM). Furthermore, in order to accurately evaluate the dispersion effect on AIF, the new complete cloud parameterizations of R e and Au explicitly accountingmore » for ε are implemented into the CAM version 5.1 (CAM5.1), and a suite of sensitivity experiments is conducted with different representations of ε reported in the literature. It is shown that the shortwave cloud radiative forcing is much better simulated with the new cloud parameterizations as compared to the standard scheme in CAM5.1, whereas the influences on longwave cloud radiative forcing and surface precipitation are minimal. In addition, consideration of the dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, especially in the Northern Hemisphere. The corresponding AIF with the dispersion effect considered can also be reduced substantially by a range of 0.10 to 0.21 W m -2 at the global scale and by a much bigger margin of 0.25 to 0.39 W m -2 for the Northern Hemisphere in comparison with that of fixed relative dispersion, mainly dependent on the change of relative dispersion and droplet concentrations (Δε/ΔN).« less

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George

2002-01-01

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

The Role of Moist Processes in the Intrinsic Predictability of Indian Ocean Cyclones

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

Taraphdar, Sourav; Mukhopadhyay, P.; Leung, Lai-Yung R.

The role of moist processes and the possibility of error cascade from cloud scale processes affecting the intrinsic predictable time scale of a high resolution convection permitting model within the environment of tropical cyclones (TCs) over the Indian region are investigated. Consistent with past studies of extra-tropical cyclones, it is demonstrated that moist processes play a major role in forecast error growth which may ultimately limit the intrinsic predictability of the TCs. Small errors in the initial conditions may grow rapidly and cascades from smaller scales to the larger scales through strong diabatic heating and nonlinearities associated with moist convection.more » Results from a suite of twin perturbation experiments for four tropical cyclones suggest that the error growth is significantly higher in cloud permitting simulation at 3.3 km resolutions compared to simulations at 3.3 km and 10 km resolution with parameterized convection. Convective parameterizations with prescribed convective time scales typically longer than the model time step allows the effects of microphysical tendencies to average out so convection responds to a smoother dynamical forcing. Without convective parameterizations, the finer-scale instabilities resolved at 3.3 km resolution and stronger vertical motion that results from the cloud microphysical parameterizations removing super-saturation at each model time step can ultimately feed the error growth in convection permitting simulations. This implies that careful considerations and/or improvements in cloud parameterizations are needed if numerical predictions are to be improved through increased model resolution. Rapid upscale error growth from convective scales may ultimately limit the intrinsic mesoscale predictability of the TCs, which further supports the needs for probabilistic forecasts of these events, even at the mesoscales.« less

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

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

Zhang, Yang; Leung, L. Ruby; Fan, Jiwen

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and globalmore » climate models.« less

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

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Jiming; Lv, Qiaoyi; Jian, Bida; Zhang, Min; Zhao, Chuanfeng; Fu, Qiang; Kawamoto, Kazuaki; Zhang, Hua

2018-05-01

Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007-2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.

Reducing Errors in Satellite Simulated Views of Clouds with an Improved Parameterization of Unresolved Scales

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Marchand, R.; Ackerman, T. P.

2016-12-01

Satellite instrument simulators have emerged as a means to reduce errors in model evaluation by producing simulated or psuedo-retrievals from model fields, which account for limitations in the satellite retrieval process. Because of the mismatch in resolved scales between satellite retrievals and large-scale models, model cloud fields must first be downscaled to scales consistent with satellite retrievals. This downscaling is analogous to that required for model radiative transfer calculations. The assumption is often made in both model radiative transfer codes and satellite simulators that the unresolved clouds follow maximum-random overlap with horizontally homogeneous cloud condensate amounts. We examine errors in simulated MISR and CloudSat retrievals that arise due to these assumptions by applying the MISR and CloudSat simulators to cloud resolving model (CRM) output generated by the Super-parameterized Community Atmosphere Model (SP-CAM). Errors are quantified by comparing simulated retrievals performed directly on the CRM fields with those simulated by first averaging the CRM fields to approximately 2-degree resolution, applying a "subcolumn generator" to regenerate psuedo-resolved cloud and precipitation condensate fields, and then applying the MISR and CloudSat simulators on the regenerated condensate fields. We show that errors due to both assumptions of maximum-random overlap and homogeneous condensate are significant (relative to uncertainties in the observations and other simulator limitations). The treatment of precipitation is particularly problematic for CloudSat-simulated radar reflectivity. We introduce an improved subcolumn generator for use with the simulators, and show that these errors can be greatly reduced by replacing the maximum-random overlap assumption with the more realistic generalized overlap and incorporating a simple parameterization of subgrid-scale cloud and precipitation condensate heterogeneity. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. SAND2016-7485 A

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.;

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.

Evaluation of WRF Model Against Satellite and Field Measurements During ARM March 2000 IOP

NASA Astrophysics Data System (ADS)

Wu, J.; Zhang, M.

2003-12-01

Meso-scale WRF model is employed to simulate the organization of clouds related with the cyclogenesis occurred during March 1-4, 2000 over ARM SGP CART site. Qualitative comparisons of simulated clouds with GOES8 satellite images show that the WRF model can capture the main features of clouds related with the cyclogenesis. The simulated precipitation patterns also match the Radar reflectivity images well. Further evaluation of the simulated features on GCM grid-scale is conducted against ARM field measurements. The evaluation shows that the evolutions of the simulated state fields such as temperature and moisture, the simulated wind fields and the derived large-scale temperature and moisture tendencies closely follow the observed patterns. These results encourages us to use meso-scale WRF model as a tool to verify the performance of GCMs in simulating cloud feedback processes related with the frontal clouds such that we can test and validate the current cloud parameterizations in climate models, and make possible improvements to different components of current cloud parameterizations in GCMs.

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

Local Interactions of Hydrometeors by Diffusion in Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Baumgartner, Manuel; Spichtinger, Peter

2017-04-01

Mixed-phase clouds, containing both ice particles and liquid droplets, are important for the Earth-Atmosphere system. They modulate the radiation budget by a combination of albedo effect and greenhouse effect. In contrast to liquid water clouds, the radiative impact of clouds containing ice particles is still uncertain. Scattering and absorption highly depends in microphysical properties of ice crystals, e.g. size and shape. In addition, most precipitation on Earth forms via the ice phase. Thus, better understanding of ice processes as well as their representation in models is required. A key process for determining shape and size of ice crystals is diffusional growth. Diffusion processes in mixed-phase clouds are highly uncertain; in addition they are usually highly simplified in cloud models, especially in bulk microphysics parameterizations. The direct interaction between cloud droplets and ice particles, due to spatial inhomogeneities, is ignored; the particles can only interact via their environmental conditions. Local effects as supply of supersaturation due to clusters of droplets around ice particles are usually not represented, although they form the physical basis of the Wegener-Bergeron-Findeisen process. We present direct numerical simulations of the interaction of single ice particles and droplets, especially their local competition for the available water vapor. In addition, we show an approach to parameterize local interactions by diffusion. The suggested parameterization uses local steady-state solutions of the diffusion equations for water vapor for an ice particle as well as a droplet. The individual solutions are coupled together to obtain the desired interaction. We show some results of the scheme as implemented in a parcel model.

A Generalized Simple Formulation of Convective Adjustment Timescale for Cumulus Convection Parameterizations

EPA Science Inventory

Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a pres...

Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval.

Evaluation of Surface Flux Parameterizations with Long-Term ARM Observations

DOE PAGES

Liu, Gang; Liu, Yangang; Endo, Satoshi

2013-02-01

Surface momentum, sensible heat, and latent heat fluxes are critical for atmospheric processes such as clouds and precipitation, and are parameterized in a variety of models ranging from cloud-resolving models to large-scale weather and climate models. However, direct evaluation of the parameterization schemes for these surface fluxes is rare due to limited observations. This study takes advantage of the long-term observations of surface fluxes collected at the Southern Great Plains site by the Department of Energy Atmospheric Radiation Measurement program to evaluate the six surface flux parameterization schemes commonly used in the Weather Research and Forecasting (WRF) model and threemore » U.S. general circulation models (GCMs). The unprecedented 7-yr-long measurements by the eddy correlation (EC) and energy balance Bowen ratio (EBBR) methods permit statistical evaluation of all six parameterizations under a variety of stability conditions, diurnal cycles, and seasonal variations. The statistical analyses show that the momentum flux parameterization agrees best with the EC observations, followed by latent heat flux, sensible heat flux, and evaporation ratio/Bowen ratio. The overall performance of the parameterizations depends on atmospheric stability, being best under neutral stratification and deteriorating toward both more stable and more unstable conditions. Further diagnostic analysis reveals that in addition to the parameterization schemes themselves, the discrepancies between observed and parameterized sensible and latent heat fluxes may stem from inadequate use of input variables such as surface temperature, moisture availability, and roughness length. The results demonstrate the need for improving the land surface models and measurements of surface properties, which would permit the evaluation of full land surface models.« less

The roles of dry convection, cloud-radiation feedback processes and the influence of recent improvements in the parameterization of convection in the GLA GCM

NASA Technical Reports Server (NTRS)

Sud, Y.; Molod, A.

1988-01-01

The Goddard Laboratory for Atmospheres GCM is used to study the sensitivity of the simulated July circulation to modifications in the parameterization of dry and moist convection, evaporation from falling raindrops, and cloud-radiation interaction. It is shown that the Arakawa-Schubert (1974) cumulus parameterization and a more realistic dry convective mixing calculation yielded a better intertropical convergence zone over North Africa than the previous convection scheme. It is found that the physical mechanism for the improvement was the upward mixing of PBL moisture by vigorous dry convective mixing. A modified rain-evaporation parameterization which accounts for raindrop size distribution, the atmospheric relative humidity, and a typical spatial rainfall intensity distribution for convective rain was developed and implemented. This scheme led to major improvements in the monthly mean vertical profiles of relative humidity and temperature, convective and large-scale cloudiness, rainfall distributions, and mean relative humidity in the PBL.

Implementation of a gust front head collapse scheme in the WRF numerical model

NASA Astrophysics Data System (ADS)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2018-05-01

Gust fronts are thunderstorm-related phenomena usually associated with severe winds which are of great importance in theoretical meteorology, weather forecasting, cloud dynamics and precipitation, and wind engineering. An important feature of gust fronts demonstrated through both theoretical and observational studies is the periodic collapse and rebuild of the gust front head. This cyclic behavior of gust fronts results in periodic forcing of vertical velocity ahead of the parent thunderstorm, which consequently influences the storm dynamics and microphysics. This paper introduces the first gust front pulsation parameterization scheme in the WRF-ARW model (Weather Research and Forecasting-Advanced Research WRF). The influence of this new scheme on model performances is tested through investigation of the characteristics of an idealized supercell cumulonimbus cloud, as well as studying a real case of thunderstorms above the United Arab Emirates. In the ideal case, WRF with the gust front scheme produced more precipitation and showed different time evolution of mixing ratios of cloud water and rain, whereas the mixing ratios of ice and graupel are almost unchanged when compared to the default WRF run without the parameterization of gust front pulsation. The included parameterization did not disturb the general characteristics of thunderstorm cloud, such as the location of updraft and downdrafts, and the overall shape of the cloud. New cloud cells in front of the parent thunderstorm are also evident in both ideal and real cases due to the included forcing of vertical velocity caused by the periodic collapse of the gust front head. Despite some differences between the two WRF simulations and satellite observations, the inclusion of the gust front parameterization scheme produced more cumuliform clouds and seem to match better with real observations. Both WRF simulations gave poor results when it comes to matching the maximum composite radar reflectivity from radar measurement. Similar to the ideal case, WRF model with the gust front scheme gave more precipitation than the default WRF run. In particular, the gust front scheme increased the area characterized with light precipitation and diminished the development of very localized and intense precipitation.

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

Rosenfeld, Daniel; Wang, Hailong; Rasch, Philip J.

Numerical simulations described in previous studies showed that adding cloud condensation nuclei to marine stratocumulus can prevent their breakup from closed into open cells. Additional analyses of the same simulations show that the suppression of rain is well described in terms of cloud drop effective radius (re). Rain is initiated when re near cloud top is around 12-14 um. Cloud water starts to get depleted when column-maximum rain intensity (Rmax) exceeds 0.1 mm h-1. This happens when cloud-top re reaches 14 um. Rmax is mostly less than 0.1 mm h-1 at re<14 um, regardless of the cloud water path, butmore » increases rapidly when re exceeds 14 um. This is in agreement with recent aircraft observations and theoretical observations in convective clouds so that the mechanism is not limited to describing marine stratocumulus. These results support the hypothesis that the onset of significant precipitation is determined by the number of nucleated cloud drops and the height (H) above cloud base within the cloud that is required for cloud drops to reach re of 14 um. In turn, this can explain the conditions for initiation of significant drizzle and opening of closed cells providing the basis for a simple parameterization for GCMs that unifies the representation of both precipitating and non-precipitating clouds as well as the transition between them. Furthermore, satellite global observations of cloud depth (from base to top), and cloud top re can be used to derive and validate this parameterization.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

An Evaluation of Lightning Flash Rate Parameterizations Based on Observations of Colorado Storms during DC3

NASA Astrophysics Data System (ADS)

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

2013-12-01

Predicting lightning activity in thunderstorms is important in order to accurately quantify the production of nitrogen oxides (NOx = NO + NO2) by lightning (LNOx). Lightning is an important global source of NOx, and since NOx is a chemical precursor to ozone, the climatological impacts of LNOx could be significant. Many cloud-resolving models rely on parameterizations to predict lightning and LNOx since the processes leading to charge separation and lightning discharge are not yet fully understood. This study evaluates predicted flash rates based on existing lightning parameterizations against flash rates observed for Colorado storms during the Deep Convective Clouds and Chemistry Experiment (DC3). Evaluating lightning parameterizations against storm observations is a useful way to possibly improve the prediction of flash rates and LNOx in models. Additionally, since convective storms that form in the eastern plains of Colorado can be different thermodynamically and electrically from storms in other regions, it is useful to test existing parameterizations against observations from these storms. We present an analysis of the dynamics, microphysics, and lightning characteristics of two case studies, severe storms that developed on 6 and 7 June 2012. This analysis includes dual-Doppler derived horizontal and vertical velocities, a hydrometeor identification based on polarimetric radar variables using the CSU-CHILL radar, and insight into the charge structure using observations from the northern Colorado Lightning Mapping Array (LMA). Flash rates were inferred from the LMA data using a flash counting algorithm. We have calculated various microphysical and dynamical parameters for these storms that have been used in empirical flash rate parameterizations. In particular, maximum vertical velocity has been used to predict flash rates in some cloud-resolving chemistry simulations. We diagnose flash rates for the 6 and 7 June storms using this parameterization and compare to observed flash rates. For the 6 June storm, a preliminary analysis of aircraft observations of storm inflow and outflow is presented in order to place flash rates (and other lightning statistics) in the context of storm chemistry. An approach to a possibly improved LNOx parameterization scheme using different lightning metrics such as flash area will be discussed.

Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.

Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis

EPA Science Inventory

This study implemented first, second and glaciations aerosol indirect effects (AIE) on resolved clouds in the two-way coupled WRF-CMAQ modeling system by including parameterizations for both cloud drop and ice number concentrations on the basis of CMAQ predicted aerosol distribu...

Sensitivity of Simulated Warm Rain Formation to Collision and Coalescence Efficiencies, Breakup, and Turbulence: Comparison of Two Bin-Resolved Numerical Models

NASA Technical Reports Server (NTRS)

Fridlind, Ann; Seifert, Axel; Ackerman, Andrew; Jensen, Eric

2004-01-01

Numerical models that resolve cloud particles into discrete mass size distributions on an Eulerian grid provide a uniquely powerful means of studying the closely coupled interaction of aerosols, cloud microphysics, and transport that determine cloud properties and evolution. However, such models require many experimentally derived paramaterizations in order to properly represent the complex interactions of droplets within turbulent flow. Many of these parameterizations remain poorly quantified, and the numerical methods of solving the equations for temporal evolution of the mass size distribution can also vary considerably in terms of efficiency and accuracy. In this work, we compare results from two size-resolved microphysics models that employ various widely-used parameterizations and numerical solution methods for several aspects of stochastic collection.

Sensitivity of CAM5-simulated Arctic clouds and radiation to ice nucleation parameterization

DOE PAGES

Xie, Shaocheng; Liu, Xiaohong; Zhao, Chuanfeng; ...

2013-08-06

Sensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and amore » decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the optical depth of Arctic clouds, which leads to a stronger cloud radiative forcing (net cooling) at the top of the atmosphere. The comparison with satellite data shows that the new scheme slightly improves low-level cloud simulations over most of the Arctic but produces too many midlevel clouds. Considerable improvements are seen in the simulated low-level clouds and their properties when compared with Arctic ground-based measurements. As a result, issues with the observations and the model–observation comparison in the Arctic region are discussed.« less

Introducing Subrid-scale Cloud Feedbacks to Radiation for Regional Meteorological and Cllimate Modeling

EPA Science Inventory

Convection systems and associated cloudiness directly influence regional and local radiation budgets, and dynamics and thermodynamics through feedbacks. However, most subgrid-scale convective parameterizations in regional weather and climate models do not consider cumulus cloud ...

Bias Reduction as Guidance for Developing Convection and Cloud Parameterization in GFDL AM4/CM4

NASA Astrophysics Data System (ADS)

Zhao, M.; Held, I.; Golaz, C.

2016-12-01

The representations of moist convection and clouds are challenging in global climate models and they are known to be important to climate simulations at all spatial and temporal scales. Many climate simulation biases can be traced to deficiencies in convection and cloud parameterizations. I will present some key biases that we are concerned about and the efforts that we have made to reduce the biases during the development of NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) new generation global climate model AM4/CM4. In particular, I will present a modified version of the moist convection scheme that is based on the University of Washington Shallow Cumulus scheme (UWShCu, Bretherton et. al 2004). The new scheme produces marked improvement in simulation of the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) compared to that used in AM3 and HIRAM. AM4/CM4 also produces high quality simulation of global distribution of cloud radiative effects and the precipitation with realistic mean climate state. This differs from models of improved MJO but with a much deteriorated mean state. The modifications to the UWShCu include an additional bulk plume for representing deep convection. The entrainment rate in the deep plume is parameterized to be a function of column-integrated relative humidity. The deep convective closure is based on relaxation of the convective available potential energy (CAPE) or cloud work function. The plumes' precipitation efficiency is optimized for better simulations of the cloud radiative effects. Precipitation re-evaporation is included in both shallow and deep plumes. In addition, a parameterization of convective gustiness is included with an energy source driven by cold pool derived from precipitation re-evaporation within the boundary layer and energy sink due to dissipation. I will present the motivations of these changes which are driven by reducing some aspects of the AM4/CM4 biases. Finally, I will also present the biases in current AM4/CM4 and challenges to further reduce them.

Multi-scale Modeling of Arctic Clouds

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A Hierarchical Modeling Study of the Interactions Among Turbulence, Cloud Microphysics, and Radiative Transfer in the Evolution of Cirrus Clouds

NASA Technical Reports Server (NTRS)

Curry, Judith; Khvorostyanov, V. I.

2005-01-01

This project used a hierarchy of cloud resolving models to address the following science issues of relevance to CRYSTAL-FACE: What ice crystal nucleation mechanisms are active in the different types of cirrus clouds in the Florida area and how do these different nucleation processes influence the evolution of the cloud system and the upper tropospheric humidity? How does the feedback between supersaturation and nucleation impact the evolution of the cloud? What is the relative importance of the large-scale vertical motion and the turbulent motions in the evolution of the crystal size spectra? How does the size spectra impact the life-cycle of the cloud, stratospheric dehydration, and cloud radiative forcing? What is the nature of the turbulence and waves in the upper troposphere generated by precipitating deep convective cloud systems? How do cirrus microphysical and optical properties vary with the small-scale dynamics? How do turbulence and waves in the upper troposphere influence the cross-tropopause mixing and stratospheric and upper tropospheric humidity? The models used in this study were: 2-D hydrostatic model with explicit microphysics that can account for 30 size bins for both the droplet and crystal size spectra. Notably, a new ice crystal nucleation scheme has been incorporated into the model. Parcel model with explicit microphysics, for developing and evaluating microphysical parameterizations. Single column model for testing bulk microphysics parameterizations

Cloud-System Resolving Models: Status and Prospects

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncreiff, Mitch

2008-01-01

Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.

Assessment of NASA GISS E2 CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations: Cloud fraction and properties

NASA Astrophysics Data System (ADS)

Stanfield, R.; Dong, X.; Xi, B.; Kennedy, A. D.; Del Genio, A. D.; Minnis, P.; Jiang, J. H.

2013-12-01

Recent changes to boundary layer turbulence and convection parameterizations of the NASA GISS E2 GCM have led to drastic improvements in the newest Post-CMIP5 (P5) model simulations. A study has been performed to evaluate these changes. Variables including Cloud Fraction (CF), Liquid Water Path (LWP), Ice Water Path (IWP), Cloud Water Path (LWP+IWP, CWP), Precipitable Water Vapor (PWV), and Relative Humidity (RH), from P5 and its CMIP5 (C5) predecessor have been compared to multiple satellite observations including CERES-MODIS (CM), CloudSat/CALIPSO (CC), AIRS, and AMSR-E. P5 simulations show drastic improvements for regional CFs, resulting in better correlations with observations. The largest improvements were found over the Southern Mid-Latitudes (SMLs), where newly implemented changes to the boundary layer turbulence parameterization increased low-level CF by ~20% while generating less optically thick clouds. The double InterTropical Convergence Zone (ITCZ) issue that plagues many GCMs, including previous GISS C5 simulations, is also removed with the new changes to convection parameterizations when decoupled from the ocean. P5 simulations show a decrease in global CWP, more closely resembling CC and CM observations. Globally, P5 simulated PWV is in better agreement with AMSR-R and AIRS, particularly over the SML oceans. RH comparisons show improvement when compared with AIRS. Spatial and variability analyses using Taylor diagrams indicate overall better correlations and smaller standard deviations in PWV and RH comparisons between P5/C5 simulations and AMSR-R/AIRS observations than CF and CWP/LWP/IWP comparisons.

Ultra-Parameterized CAM: Progress Towards Low-Cloud Permitting Superparameterization

NASA Astrophysics Data System (ADS)

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

2016-12-01

A leading source of uncertainty in climate feedback arises from the representation of low clouds, which are not resolved but depend on small-scale physical processes (e.g. entrainment, boundary layer turbulence) that are heavily parameterized. We show results from recent attempts to achieve an explicit representation of low clouds by pushing the computational limits of cloud superparameterization to resolve boundary-layer eddy scales relevant to marine stratocumulus (250m horizontal and 20m vertical length scales). This extreme configuration is called "ultraparameterization". Effects of varying horizontal vs. vertical resolution are analyzed in the context of altered constraints on the turbulent kinetic energy statistics of the marine boundary layer. We show that 250m embedded horizontal resolution leads to a more realistic boundary layer vertical structure, but also to an unrealistic cloud pulsation that cannibalizes time mean LWP. We explore the hypothesis that feedbacks involving horizontal advection (not typically encountered in offline LES that neglect this degree of freedom) may conspire to produce such effects and present strategies to compensate. The results are relevant to understanding the emergent behavior of quasi-resolved low cloud decks in a multi-scale modeling framework within a previously unencountered grey zone of better resolved boundary-layer turbulence.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Modeling the clouds on Venus: model development and improvement of a nucleation parameterization

NASA Astrophysics Data System (ADS)

Määttänen, Anni; Bekki, Slimane; Vehkamäki, Hanna; Julin, Jan; Montmessin, Franck; Ortega, Ismael K.; Lebonnois, Sébastien

2014-05-01

As both the clouds of Venus and aerosols in the Earth's stratosphere are composed of sulfuric acid droplets, we use the 1-D version of a model [1,4] developed for stratospheric aerosols and clouds to study the clouds on Venus. We have removed processes and compounds related to the stratospheric clouds so that the only species remaining are water and sulfuric acid, corresponding to the stratospheric sulfate aerosols, and we have added some key processes. The model describes microphysical processes including condensation/evaporation, and sedimentation. Coagulation, turbulent diffusion, and a parameterization for two-component nucleation [8] of water and sulfuric acid have been added in the model. Since the model describes explicitly the size distribution with a large number of size bins (50-500), it can handle multiple particle modes. The validity ranges of the existing nucleation parameterization [7] have been improved to cover a larger temperature range, and the very low relative humidity (RH) and high sulfuric acid concentrations found in the atmosphere of Venus. We have made several modifications to improve the 2002 nucleation parameterization [7], most notably ensuring that the two-component nucleation model behaves as predicted by the analytical studies at the one-component limit reached at extremely low RH. We have also chosen to use a self-consistent cluster distribution [9], constrained by scaling it to recent quantum chemistry calculations [3]. First tests of the cloud model have been carried out with temperature profiles from VIRA [2] and from the LMD Venus GCM [5], and with a compilation of water vapor and sulfuric acid profiles, as in [6]. The temperature and pressure profiles do not evolve with time, but the vapour profiles naturally change with the cloud. However, no chemistry is included for the moment, so the vapor concentrations are only dependent on the microphysical processes. The model has been run for several hundreds of Earth days to reach a steady state. Preliminary results are evaluated against observations. [1] Jumelet et al., JGR, 2009. [2] Kliore et al., 1986. [3] Kurtén et al., BER, 2007 [4] Larsen et al., JGR, 2000. [5] Lebonnois et al. JGR, 2010. [6] McGouldrick and Toon, Icarus 191, 2007. [7] Vehkamäki et al. JGR, 2002 [9] Wilemski and Wyslouzil, J.Chem.Phys. 1995.

Final Report for “Simulating the Arctic Winter Longwave Indirect Effects. A New Parameterization for Frost Flower Aerosol Salt Emissions” (DESC0006679) for 9/15/2011 through 9/14/2015

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

Russell, Lynn M.; Somerville, Richard C.J.; Burrows, Susannah

Description of the Project: This project has improved the aerosol formulation in a global climate model by using innovative new field and laboratory observations to develop and implement a novel wind-driven sea ice aerosol flux parameterization. This work fills a critical gap in the understanding of clouds, aerosol, and radiation in polar regions by addressing one of the largest missing particle sources in aerosol-climate modeling. Recent measurements of Arctic organic and inorganic aerosol indicate that the largest source of natural aerosol during the Arctic winter is emitted from crystal structures, known as frost flowers, formed on a newly frozen seamore » ice surface [Shaw et al., 2010]. We have implemented the new parameterization in an updated climate model making it the first capable of investigating how polar natural aerosol-cloud indirect effects relate to this important and previously unrecognized sea ice source. The parameterization is constrained by Arctic ARM in situ cloud and radiation data. The modified climate model has been used to quantify the potential pan-Arctic radiative forcing and aerosol indirect effects due to this missing source. This research supported the work of one postdoc (Li Xu) for two years and contributed to the training and research of an undergraduate student. This research allowed us to establish a collaboration between SIO and PNNL in order to contribute the frost flower parameterization to the new ACME model. One peer-reviewed publications has already resulted from this work, and a manuscript for a second publication has been completed. Additional publications from the PNNL collaboration are expected to follow.« less

New particle dependant parameterizations of heterogeneous freezing processes.

NASA Astrophysics Data System (ADS)

Diehl, Karoline; Mitra, Subir K.

2014-05-01

For detailed investigations of cloud microphysical processes an adiabatic air parcel model with entrainment is used. It represents a spectral bin model which explicitly solves the microphysical equations. The initiation of the ice phase is parameterized and describes the effects of different types of ice nuclei (mineral dust, soot, biological particles) in immersion, contact, and deposition modes. As part of the research group INUIT (Ice Nuclei research UnIT), existing parameterizations have been modified for the present studies and new parameterizations have been developed mainly on the basis of the outcome of INUIT experiments. Deposition freezing in the model is dependant on the presence of dry particles and on ice supersaturation. The description of contact freezing combines the collision kernel of dry particles with the fraction of frozen drops as function of temperature and particle size. A new parameterization of immersion freezing has been coupled to the mass of insoluble particles contained in the drops using measured numbers of ice active sites per unit mass. Sensitivity studies have been performed with a convective temperature and dew point profile and with two dry aerosol particle number size distributions. Single and coupled freezing processes are studied with different types of ice nuclei (e.g., bacteria, illite, kaolinite, feldspar). The strength of convection is varied so that the simulated cloud reaches different levels of temperature. As a parameter to evaluate the results the ice water fraction is selected which is defined as the relation of the ice water content to the total water content. Ice water fractions between 0.1 and 0.9 represent mixed-phase clouds, larger than 0.9 ice clouds. The results indicate the sensitive parameters for the formation of mixed-phase and ice clouds are: 1. broad particle number size distribution with high number of small particles, 2. temperatures below -25°C, 3. specific mineral dust particles as ice nuclei such as illite or montmorillonite. Coupled cases of deposition and contact freezing show that they are hardly in competition because of differences in the preferred particle sizes. In the contact mode, small particles are less efficient for collisions as well as less efficient as ice nuclei so that these are available for deposition freezing. On the other hand, immersion freezing is the dominant process when it is coupled with deposition freezing. As it is initiated earlier the formed ice particles consume water vapor for growing. The competition of combined contact and immersion freezing leads to lower ice water contents because more ice particles are formed via the immersion mode. In general, ice clouds and mixed-phase clouds with high ice water fractions are not directly the result of primary ice formation but of secondary ice formation and growth of ice particles at the expense of liquid drops.

A Flexible Parameterization for Shortwave Optical Properties of Ice Crystals

NASA Technical Reports Server (NTRS)

VanDiedenhoven, Bastiaan; Ackerman, Andrew S.; Cairns, Brian; Fridlind, Ann M.

2014-01-01

A parameterization is presented that provides extinction cross section sigma (sub e), single-scattering albedo omega, and asymmetry parameter (g) of ice crystals for any combination of volume, projected area, aspect ratio, and crystal distortion at any wavelength in the shortwave. Similar to previous parameterizations, the scheme makes use of geometric optics approximations and the observation that optical properties of complex, aggregated ice crystals can be well approximated by those of single hexagonal crystals with varying size, aspect ratio, and distortion levels. In the standard geometric optics implementation used here, sigma (sub e) is always twice the particle projected area. It is shown that omega is largely determined by the newly defined absorption size parameter and the particle aspect ratio. These dependences are parameterized using a combination of exponential, lognormal, and polynomial functions. The variation of (g) with aspect ratio and crystal distortion is parameterized for one reference wavelength using a combination of several polynomials. The dependences of g on refractive index and omega are investigated and factors are determined to scale the parameterized (g) to provide values appropriate for other wavelengths. The parameterization scheme consists of only 88 coefficients. The scheme is tested for a large variety of hexagonal crystals in several wavelength bands from 0.2 to 4 micron, revealing absolute differences with reference calculations of omega and (g) that are both generally below 0.015. Over a large variety of cloud conditions, the resulting root-mean-squared differences with reference calculations of cloud reflectance, transmittance, and absorptance are 1.4%, 1.1%, and 3.4%, respectively. Some practical applications of the parameterization in atmospheric models are highlighted.

Double-moment cloud microphysics scheme for the deep convection parameterization in the GFDL AM3

NASA Astrophysics Data System (ADS)

Belochitski, A.; Donner, L.

2014-12-01

A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) has been implemented in to the Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Such detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and their roles in climate change. The scheme is first tested in the single column version of the GFDL AM3 using forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes site. Scheme's impact on SCM simulations is discussed. As the next step, runs of the full atmospheric GCM incorporating the new parameterization are compared to the unmodified version of GFDL AM3. Global climatological fields and their variability are contrasted with those of the original version of the GCM. Impact on cloud radiative forcing and climate sensitivity is investigated.

Double-moment Cloud Microphysics Scheme for the Deep Convection Parameterization in the GFDL AM3

NASA Astrophysics Data System (ADS)

Belochitski, A.; Donner, L.

2013-12-01

A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) is being implemented in to the deep convection parameterization of Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and the roles of these effects in climate change. The scheme is implemented into the single column version of the GFDL AM3 and evaluated using large scale forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes and Tropical West Pacific sites. Sensitivity of the scheme to formulations for autoconversion of cloud water and its accretion by rain, self-collection of rain and self-collection of snow, as well as the formulation for heterogenous ice nucleation is investigated. In the future, tests with the full atmospheric GCM will be conducted.

Self-consistency tests of large-scale dynamics parameterizations for single-column modeling

DOE PAGES

Edman, Jacob P.; Romps, David M.

2015-03-18

Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less

On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

DOE PAGES

McCoy, Daniel T.; Tan, Ivy; Hartmann, Dennis L.; ...

2016-05-06

In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water wouldmore » also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.« less

A Heuristic Parameterization for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2017-10-01

The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single-merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

Scaling analysis of cloud and rain water in marine stratocumulus and implications for scale-aware microphysical parameterizations

NASA Astrophysics Data System (ADS)

Witte, M.; Morrison, H.; Jensen, J. B.; Bansemer, A.; Gettelman, A.

2017-12-01

The spatial covariance of cloud and rain water (or in simpler terms, small and large drops, respectively) is an important quantity for accurate prediction of the accretion rate in bulk microphysical parameterizations that account for subgrid variability using assumed probability density functions (pdfs). Past diagnoses of this covariance from remote sensing, in situ measurements and large eddy simulation output have implicitly assumed that the magnitude of the covariance is insensitive to grain size (i.e. horizontal resolution) and averaging length, but this is not the case because both cloud and rain water exhibit scale invariance across a wide range of scales - from tens of centimeters to tens of kilometers in the case of cloud water, a range that we will show is primarily limited by instrumentation and sampling issues. Since the individual variances systematically vary as a function of spatial scale, it should be expected that the covariance follows a similar relationship. In this study, we quantify the scaling properties of cloud and rain water content and their covariability from high frequency in situ aircraft measurements of marine stratocumulus taken over the southeastern Pacific Ocean aboard the NSF/NCAR C-130 during the VOCALS-REx field experiment of October-November 2008. First we confirm that cloud and rain water scale in distinct manners, indicating that there is a statistically and potentially physically significant difference in the spatial structure of the two fields. Next, we demonstrate that the covariance is a strong function of spatial scale, which implies important caveats regarding the ability of limited-area models with domains smaller than a few tens of kilometers across to accurately reproduce the spatial organization of precipitation. Finally, we present preliminary work on the development of a scale-aware parameterization of cloud-rain water subgrid covariability based in multifractal analysis intended for application in large-scale model microphysics schemes.

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

NASA Technical Reports Server (NTRS)

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua

2015-01-01

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

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

DOE PAGES

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; ...

2015-06-19

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only amore » relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.« less

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

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

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.

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

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

DOE PAGES

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; ...

2017-06-19

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Impact of stratospheric aircraft on calculations of nitric acid trihydrate cloud surface area densities using NMC temperatures and 2D model constituent distributions

NASA Technical Reports Server (NTRS)

Considine, David B.; Douglass, Anne R.

1994-01-01

A parameterization of NAT (nitric acid trihydrate) clouds is developed for use in 2D models of the stratosphere. The parameterization uses model distributions of HNO3 and H2O to determine critical temperatures for NAT formation as a function of latitude and pressure. National Meteorological Center temperature fields are then used to determine monthly temperature frequency distributions, also as a function of latitude and pressure. The fractions of these distributions which fall below the critical temperatures for NAT formation are then used to determine the NAT cloud surface area density for each location in the model grid. By specifying heterogeneous reaction rates as functions of the surface area density, it is then possible to assess the effects of the NAT clouds on model constituent distributions. We also consider the increase in the NAT cloud formation in the presence of a fleet of stratospheric aircraft. The stratospheric aircraft NO(x) and H2O perturbations result in increased HNO3 as well as H2O. This increases the probability of NAT formation substantially, especially if it is assumed that the aircraft perturbations are confined to a corridor region.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

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

NASA Astrophysics Data System (ADS)

Remillard, J.

2015-12-01

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

Cirrus cloud model parameterizations: Incorporating realistic ice particle generation

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

A Comparison of Parameterizations of Secondary Organic Aerosol Production: Global Budget and Spatiotemporal Variability

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S.

2014-12-01

Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols.

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

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

2010-01-01

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.

NASA Astrophysics Data System (ADS)

Gubler, S.; Gruber, S.; Purves, R. S.

2012-06-01

As many environmental models rely on simulating the energy balance at the Earth's surface based on parameterized radiative fluxes, knowledge of the inherent model uncertainties is important. In this study we evaluate one parameterization of clear-sky direct, diffuse and global shortwave downward radiation (SDR) and diverse parameterizations of clear-sky and all-sky longwave downward radiation (LDR). In a first step, SDR is estimated based on measured input variables and estimated atmospheric parameters for hourly time steps during the years 1996 to 2008. Model behaviour is validated using the high quality measurements of six Alpine Surface Radiation Budget (ASRB) stations in Switzerland covering different elevations, and measurements of the Swiss Alpine Climate Radiation Monitoring network (SACRaM) in Payerne. In a next step, twelve clear-sky LDR parameterizations are calibrated using the ASRB measurements. One of the best performing parameterizations is elected to estimate all-sky LDR, where cloud transmissivity is estimated using measured and modeled global SDR during daytime. In a last step, the performance of several interpolation methods is evaluated to determine the cloud transmissivity in the night. We show that clear-sky direct, diffuse and global SDR is adequately represented by the model when using measurements of the atmospheric parameters precipitable water and aerosol content at Payerne. If the atmospheric parameters are estimated and used as a fix value, the relative mean bias deviance (MBD) and the relative root mean squared deviance (RMSD) of the clear-sky global SDR scatter between between -2 and 5%, and 7 and 13% within the six locations. The small errors in clear-sky global SDR can be attributed to compensating effects of modeled direct and diffuse SDR since an overestimation of aerosol content in the atmosphere results in underestimating the direct, but overestimating the diffuse SDR. Calibration of LDR parameterizations to local conditions reduces MBD and RMSD strongly compared to using the published values of the parameters, resulting in relative MBD and RMSD of less than 5% respectively 10% for the best parameterizations. The best results to estimate cloud transmissivity during nighttime were obtained by linearly interpolating the average of the cloud transmissivity of the four hours of the preceeding afternoon and the following morning. Model uncertainty can be caused by different errors such as code implementation, errors in input data and in estimated parameters, etc. The influence of the latter (errors in input data and model parameter uncertainty) on model outputs is determined using Monte Carlo. Model uncertainty is provided as the relative standard deviation σrel of the simulated frequency distributions of the model outputs. An optimistic estimate of the relative uncertainty σrel resulted in 10% for the clear-sky direct, 30% for diffuse, 3% for global SDR, and 3% for the fitted all-sky LDR.

Incorporation of new particle formation and early growth treatments into WRF/Chem: Model improvement, evaluation, and impacts of anthropogenic aerosols over East Asia

NASA Astrophysics Data System (ADS)

Cai, Changjie; Zhang, Xin; Wang, Kai; Zhang, Yang; Wang, Litao; Zhang, Qiang; Duan, Fengkui; He, Kebin; Yu, Shao-Cai

2016-01-01

New particle formation (NPF) provides an important source of aerosol particles and cloud condensation nuclei, which may result in enhanced cloud droplet number concentration (CDNC) and cloud shortwave albedo. In this work, several nucleation parameterizations and one particle early growth parameterization are implemented into the online-coupled Weather Research and Forecasting model coupled with chemistry (WRF/Chem) to improve the model's capability in simulating NPF and early growth of ultrafine particles over East Asia. The default 8-bin over the size range of 39 nm-10 μm used in the Model for Simulating Aerosol Interactions and Chemistry aerosol module is expanded to the 12-bin over 1 nm-10 μm to explicitly track the formation and evolution of new particles. Although model biases remain in simulating H2SO4, condensation sink, growth rate, and formation rate, the evaluation of July 2008 simulation identifies a combination of three nucleation parameterizations (i.e., COMB) that can best represent the atmospheric nucleation processes in terms of both surface nucleation events and the resulting vertical distribution of ultrafine particle concentrations. COMB consists of a power law of Wang et al. (2011) based on activation theory for urban areas in planetary boundary layer (PBL), a power law of Boy et al. (2008) based on activation theory for non-urban areas in PBL, and the ion-mediated nucleation parameterization of YU10 for above PBL. The application and evaluation of the improved model with 12-bin and the COMB nucleation parameterization in East Asia during January, April, July, and October in 2001 show that the model has an overall reasonably good skill in reproducing most observed meteorological variables and surface and column chemical concentrations. Relatively large biases in simulated precipitation and wind speeds are due to inaccurate surface roughness and limitations in model treatments of cloud formation and aerosol-cloud-precipitation interactions. Large biases in the simulated surface concentrations of PM10, NOx, CO, SO2, and VOCs at some sites are due in part to possible underestimations of emissions and in part to inaccurate meteorological predictions. The simulations of 2001 show that anthropogenic aerosols can increase aerosol optical depth by 64.0-228.3%, CDNC by 40.2-76.4%, and cloud optical thickness by 14.3-25.3%; they can reduce surface net shortwave radiation by up to 42.5-52.8 W m-2, 2-m temperature by up to 0.34-0.83 °C, and PBL height by up to 76.8-125.9 m. Such effects are more significant than those previously reported for the U.S. and Europe.

A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models

NASA Astrophysics Data System (ADS)

Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.

2016-12-01

Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.

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

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

Explicit simulation of a midlatitude Mesoscale Convective System

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

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

NASA Astrophysics Data System (ADS)

Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

2016-02-01

The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Modeling the relative contributions of secondary ice formation processes to ice crystal number concentrations within mixed-phase clouds

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Hoose, Corinna; Nenes, Athanasios

2016-04-01

Measurements of in-cloud ice crystal number concentrations can be three or four orders of magnitude greater than the in-cloud ice nuclei number concentrations. This discrepancy can be explained by various secondary ice formation processes, which occur after initial ice nucleation, but the relative importance of these processes, and even the exact physics of each, is still unclear. A simple bin microphysics model (2IM) is constructed to investigate these knowledge gaps. 2IM extends the time-lag collision parameterization of Yano and Phillips, 2011 to include rime splintering, ice-ice aggregation, and droplet shattering and to incorporate the aspect ratio evolution as in Jensen and Harrington, 2015. The relative contribution of the secondary processes under various conditions are shown. In particular, temperature-dependent efficiencies are adjusted for ice-ice aggregation versus collision around -15°C, when rime splintering is no longer active, and the effect of aspect ratio on the process weighting is explored. The resulting simulations are intended to guide secondary ice formation parameterizations in larger-scale mixed-phase cloud schemes.

Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

NASA Astrophysics Data System (ADS)

Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

2018-04-01

A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

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.

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.

Investigating the Sensitivity of Nucleation Parameterization on Ice Growth

NASA Astrophysics Data System (ADS)

Gaudet, L.; Sulia, K. J.

2017-12-01

The accurate prediction of precipitation from lake-effect snow events associated with the Great Lakes region depends on the parameterization of thermodynamic and microphysical processes, including the formation and subsequent growth of frozen hydrometeors. More specifically, the formation of ice hydrometeors has been represented through varying forms of ice nucleation parameterizations considering the different nucleation modes (e.g., deposition, condensation-freezing, homogeneous). These parameterizations have been developed from in-situ measurements and laboratory observations. A suite of nucleation parameterizations consisting of those published in Meyers et al. (1992) and DeMott et al. (2010) as well as varying ice nuclei data sources are coupled with the Adaptive Habit Model (AHM, Harrington et al. 2013), a microphysics module where ice crystal aspect ratio and density are predicted and evolve in time. Simulations are run with the AHM which is implemented in the Weather Research and Forecasting (WRF) model to investigate the effect of ice nucleation parameterization on the non-spherical growth and evolution of ice crystals and the subsequent effects on liquid-ice cloud-phase partitioning. Specific lake-effect storms that were observed during the Ontario Winter Lake-Effect Systems (OWLeS) field campaign (Kristovich et al. 2017) are examined to elucidate this potential microphysical effect. Analysis of these modeled events is aided by dual-polarization radar data from the WSR-88D in Montague, New York (KTYX). This enables a comparison of the modeled and observed polarmetric and microphysical profiles of the lake-effect clouds, which involves investigating signatures of reflectivity, specific differential phase, correlation coefficient, and differential reflectivity. Microphysical features of lake-effect bands, such as ice, snow, and liquid mixing ratios, ice crystal aspect ratio, and ice density are analyzed to understand signatures in the aforementioned modeled dual-polarization radar variables. Hence, this research helps to determine an ice nucleation scheme that will best model observations of lake-effect clouds producing snow off of Lake Ontario and Lake Erie, and analyses will highlight the sensitivity of the evolution of the cases to a given nucleation scheme.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

THOR: A New Higher-Order Closure Assumed PDF Subgrid-Scale Parameterization; Evaluation and Application to Low Cloud Feedbacks

NASA Astrophysics Data System (ADS)

Firl, G. J.; Randall, D. A.

2013-12-01

The so-called "assumed probability density function (PDF)" approach to subgrid-scale (SGS) parameterization has shown to be a promising method for more accurately representing boundary layer cloudiness under a wide range of conditions. A new parameterization has been developed, named the Two-and-a-Half ORder closure (THOR), that combines this approach with a higher-order turbulence closure. THOR predicts the time evolution of the turbulence kinetic energy components, the variance of ice-liquid water potential temperature (θil) and total non-precipitating water mixing ratio (qt) and the covariance between the two, and the vertical fluxes of horizontal momentum, θil, and qt. Ten corresponding third-order moments in addition to the skewnesses of θil and qt are calculated using diagnostic functions assuming negligible time tendencies. The statistical moments are used to define a trivariate double Gaussian PDF among vertical velocity, θil, and qt. The first three statistical moments of each variable are used to estimate the two Gaussian plume means, variances, and weights. Unlike previous similar models, plume variances are not assumed to be equal or zero. Instead, they are parameterized using the idea that the less dominant Gaussian plume (typically representing the updraft-containing portion of a grid cell) has greater variance than the dominant plume (typically representing the "environmental" or slowly subsiding portion of a grid cell). Correlations among the three variables are calculated using the appropriate covariance moments, and both plume correlations are assumed to be equal. The diagnosed PDF in each grid cell is used to calculate SGS condensation, SGS fluxes of cloud water species, SGS buoyancy terms, and to inform other physical parameterizations about SGS variability. SGS condensation is extended from previous similar models to include condensation over both liquid and ice substrates, dependent on the grid cell temperature. Implementations have been included in THOR to drive existing microphysical and radiation parameterizations with samples drawn from the trivariate PDF. THOR has been tested in a single-column model framework using standardized test cases spanning a range of large-scale conditions conducive to both shallow cumulus and stratocumulus clouds and the transition between the two states. The results were compared to published LES intercomparison results using the same cases, and the gross characteristics of both cloudiness and boundary layer turbulence produced by THOR were within the range of results from the respective LES ensembles. In addition, THOR was used in a single-column model framework to study low cloud feedbacks in the northeastern Pacific Ocean. Using initialization and forcings developed as part of the CGILS project, THOR was run at 8 points along a cross-section from the trade-wind cumulus region east of Hawaii to the coastal stratocumulus region off the coast of California for both the control climate and a climate perturbed by +2K SST. A neutral to weakly positive cloud feedback of 0-4 W m-2 K-1 was simulated along the cross-section. The physical mechanisms responsible appeared to be increased boundary layer entrainment and stratocumulus decoupling leading to reduced maximum cloud cover and liquid water path.

Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations

NASA Astrophysics Data System (ADS)

Rusli, Stephanie P.; Donovan, David P.; Russchenberg, Herman W. J.

2017-12-01

Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parameterization are used in an optimal-estimation-type framework in order to retrieve the best estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud-drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived using the three independent methods.

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

NASA Astrophysics Data System (ADS)

Kao, C.-Y. J.; Smith, W. S.

1999-05-01

A physically based cloud parameterization package, which includes the Arakawa-Schubert (AS) scheme for subgrid-scale convective clouds and the Sundqvist (SUN) scheme for nonconvective grid-scale layered clouds (hereafter referred to as the SUNAS cloud package), is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, Version 2 (CCM2). The AS scheme is used for a more reasonable heating distribution due to convective clouds and their associated precipitation. The SUN scheme allows for the prognostic computation of cloud water so that the cloud optical properties are more physically determined for shortwave and longwave radiation calculations. In addition, the formation of anvil-like clouds from deep convective systems is able to be simulated with the SUNAS package. A 10-year simulation spanning the period from 1980 to 1989 is conducted, and the effect of the cloud package on the January climate is assessed by comparing it with various available data sets and the National Center for Environmental Protection/NCAR reanalysis. Strengths and deficiencies of both the SUN and AS methods are identified and discussed. The AS scheme improves some aspects of the model dynamics and precipitation, especially with respect to the Pacific North America (PNA) pattern. CCM2's tendency to produce a westward bias of the 500 mbar stationary wave (time-averaged zonal anomalies) in the PNA sector is remedied apparently because of a less "locked-in" heating pattern in the tropics. The additional degree of freedom added by the prognostic calculation of cloud water in the SUN scheme produces interesting results in the modeled cloud and radiation fields compared with data. In general, too little cloud water forms in the tropics, while excessive cloud cover and cloud liquid water are simulated in midlatitudes. This results in a somewhat degraded simulation of the radiation budget. The overall simulated precipitation by the SUNAS package is, however, substantially improved over the original CCM2.

Parameterizing Size Distribution in Ice Clouds

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

DeSlover, Daniel; Mitchell, David L.

2009-09-25

PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD).more » Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 µm) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 µm wavelength relative to 11 µm wavelength due to the process of wave resonance or photon tunneling more active at 12 µm. This makes the 12/11 µm absorption optical depth ratio (or equivalently the 12/11 µm Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.« less

A unified view of convective transports by stratocumulus clouds, shallow cumulus clouds, and deep convection

NASA Technical Reports Server (NTRS)

Randall, David A.

1990-01-01

A bulk planetary boundary layer (PBL) model was developed with a simple internal vertical structure and a simple second-order closure, designed for use as a PBL parameterization in a large-scale model. The model allows the mean fields to vary with height within the PBL, and so must address the vertical profiles of the turbulent fluxes, going beyond the usual mixed-layer assumption that the fluxes of conservative variables are linear with height. This is accomplished using the same convective mass flux approach that has also been used in cumulus parameterizations. The purpose is to show that such a mass flux model can include, in a single framework, the compensating subsidence concept, downgradient mixing, and well-mixed layers.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Technical Reports Server (NTRS)

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

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.

Grid-scale Indirect Radiative Forcing of Climate due to aerosols over the northern hemisphere simulated by the integrated WRF-CMAQ model: Preliminary results

EPA Science Inventory

In this study, indirect aerosol effects on grid-scale clouds were implemented in the integrated WRF3.3-CMAQ5.0 modeling system by including parameterizations for both cloud droplet and ice number concentrations calculated from the CMAQ-predicted aerosol particles. The resulting c...

The effect of mineral dust and soot aerosols on ice microphysics near the foothills of the Himalayas: A numerical investigation

NASA Astrophysics Data System (ADS)

Hazra, Anupam; Padmakumari, B.; Maheskumar, R. S.; Chen, Jen-Ping

2016-05-01

This study investigates the influence of different ice nuclei (IN) species and their number concentrations on cloud ice production. The numerical simulation with different species of ice nuclei is investigated using an explicit bulk-water microphysical scheme in a Mesoscale Meteorological Model version 5 (MM5). The species dependent ice nucleation parameterization that is based on the classical nucleation theory has been implemented into the model. The IN species considered include dust and soot with two different concentrations (Low and High). The simulated cloud microphysical properties like droplet number concentration and droplet effective radii as well as macro-properties (equivalent potential temperature and relative humidity) are comparable with aircraft observations. When higher dust IN concentrations are considered, the simulation results showed good agreement with the cloud ice and cloud water mixing ratio from aircraft measurements during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. Relative importance of IN species is shown as compared to the homogeneous freezing nucleation process. The tendency of cloud ice production rates is also analyzed and found that dust IN is more efficient in producing cloud ice when compared to soot IN. The dust IN with high concentration can produce more surface precipitation than soot IN at the same concentration. This study highlights the need to improve the ice nucleation parameterization in numerical models.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

On the usage of classical nucleation theory in quantification of the impact of bacterial INP on weather and climate

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Wex, Heike; Gosewinkel, Ulrich; Šantl-Temkiv, Tina; Nielsen, Niels W.; Finster, Kai; Sørensen, Jens H.; Stratmann, Frank; Korsholm, Ulrik S.

2016-08-01

Bacterial ice-nucleating particles (INP) are present in the atmosphere and efficient in heterogeneous ice-nucleation at temperatures up to -2 °C in mixed-phase clouds. However, due to their low emission rates, their climatic impact was considered insignificant in previous modeling studies. In view of uncertainties about the actual atmospheric emission rates and concentrations of bacterial INP, it is important to re-investigate the threshold fraction of cloud droplets containing bacterial INP for a pronounced effect on ice-nucleation, by using a suitable parameterization that describes the ice-nucleation process by bacterial INP properly. Therefore, we compared two heterogeneous ice-nucleation rate parameterizations, denoted CH08 and HOO10 herein, both of which are based on classical-nucleation-theory and measurements, and use similar equations, but different parameters, to an empirical parameterization, denoted HAR13 herein, which considers implicitly the number of bacterial INP. All parameterizations were used to calculate the ice-nucleation probability offline. HAR13 and HOO10 were implemented and tested in a one-dimensional version of a weather-forecast-model in two meteorological cases. Ice-nucleation-probabilities based on HAR13 and CH08 were similar, in spite of their different derivation, and were higher than those based on HOO10. This study shows the importance of the method of parameterization and of the input variable, number of bacterial INP, for accurately assessing their role in meteorological and climatic processes.

Highly parameterized model calibration with cloud computing: an example of regional flow model calibration in northeast Alberta, Canada

NASA Astrophysics Data System (ADS)

Hayley, Kevin; Schumacher, J.; MacMillan, G. J.; Boutin, L. C.

2014-05-01

Expanding groundwater datasets collected by automated sensors, and improved groundwater databases, have caused a rapid increase in calibration data available for groundwater modeling projects. Improved methods of subsurface characterization have increased the need for model complexity to represent geological and hydrogeological interpretations. The larger calibration datasets and the need for meaningful predictive uncertainty analysis have both increased the degree of parameterization necessary during model calibration. Due to these competing demands, modern groundwater modeling efforts require a massive degree of parallelization in order to remain computationally tractable. A methodology for the calibration of highly parameterized, computationally expensive models using the Amazon EC2 cloud computing service is presented. The calibration of a regional-scale model of groundwater flow in Alberta, Canada, is provided as an example. The model covers a 30,865-km2 domain and includes 28 hydrostratigraphic units. Aquifer properties were calibrated to more than 1,500 static hydraulic head measurements and 10 years of measurements during industrial groundwater use. Three regionally extensive aquifers were parameterized (with spatially variable hydraulic conductivity fields), as was the aerial recharge boundary condition, leading to 450 adjustable parameters in total. The PEST-based model calibration was parallelized on up to 250 computing nodes located on Amazon's EC2 servers.

Probing aerosol indirect effect on deep convection using idealized cloud-resolving simulations with parameterized large-scale dynamics.

NASA Astrophysics Data System (ADS)

Anber, U.; Wang, S.; Gentine, P.; Jensen, M. P.

2017-12-01

A framework is introduced to investigate the indirect impact of aerosol loading on tropical deep convection using 3-dimentional idealized cloud-system resolving simulations with coupled large-scale circulation. The large scale dynamics is parameterized using a spectral weak temperature gradient approximation that utilizes the dominant balance in the tropics between adiabatic cooling and diabatic heating. Aerosol loading effect is examined by varying the number concentration of nuclei (CCN) to form cloud droplets in the bulk microphysics scheme over a wide range from 30 to 5000 without including any radiative effect as the radiative cooling is prescribed at a constant rate, to isolate the microphysical effect. Increasing aerosol number concentration causes mean precipitation to decrease monotonically, despite the increase in cloud condensates. Such reduction in precipitation efficiency is attributed to reduction in the surface enthalpy fluxes, and not to the divergent circulation, as the gross moist stability remains unchanged. We drive a simple scaling argument based on the moist static energy budget, that enables a direct estimation of changes in precipitation given known changes in surfaces enthalpy fluxes and the constant gross moist stability. The impact on cloud hydrometers and microphysical properties is also examined and is consistent with the macro-physical picture.

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

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2016-01-05

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

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

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

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

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

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).

Factors governing the total rainfall yield from continental convective clouds

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Gagin, Abraham

1989-01-01

Several important factors that govern the total rainfall from continental convective clouds were investigated by tracking thousands of convective cells in Israel and South Africa. The rainfall volume yield (Rvol) of the individual cells that build convective rain systems has been shown to depend mainly on the cloud-top height. There is, however, considerable variability in this relationship. The following factors that influence the Rvol were parameterized and quantitatively analyzed: (1) cloud base temperature, (2)atmospheric instability, and (3) the extent of isolation of the cell. It is also shown that a strong low level forcing increases the duration of Rvol of clouds reaching the same vertical extent.

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Technical Reports Server (NTRS)

Elsaesser, Greg; Del Genio, Anthony

2015-01-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high latitude ice IWP that decreased by 50 relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by 15 in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of 2. This was largely driven by IWC in deep-convecting regions of the tropics.Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter.GCM simulations with the improved convective parameterization yield a 50 decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Astrophysics Data System (ADS)

Elsaesser, G.; Del Genio, A. D.

2015-12-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high-latitude ice IWP that decreased by ~50% relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by ~15% in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (~200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of ~2. This was largely driven by IWC in deep-convecting regions of the tropics. Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter. GCM simulations with the improved convective parameterization yield a ~50% decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

Ice-nucleating particle emissions from photochemically aged diesel and biodiesel exhaust

NASA Astrophysics Data System (ADS)

Schill, G. P.; Jathar, S. H.; Kodros, J. K.; Levin, E. J. T.; Galang, A. M.; Friedman, B.; Link, M. F.; Farmer, D. K.; Pierce, J. R.; Kreidenweis, S. M.; DeMott, P. J.

2016-05-01

Immersion-mode ice-nucleating particle (INP) concentrations from an off-road diesel engine were measured using a continuous-flow diffusion chamber at -30°C. Both petrodiesel and biodiesel were utilized, and the exhaust was aged up to 1.5 photochemically equivalent days using an oxidative flow reactor. We found that aged and unaged diesel exhaust of both fuels is not likely to contribute to atmospheric INP concentrations at mixed-phase cloud conditions. To explore this further, a new limit-of-detection parameterization for ice nucleation on diesel exhaust was developed. Using a global-chemical transport model, potential black carbon INP (INPBC) concentrations were determined using a current literature INPBC parameterization and the limit-of-detection parameterization. Model outputs indicate that the current literature parameterization likely overemphasizes INPBC concentrations, especially in the Northern Hemisphere. These results highlight the need to integrate new INPBC parameterizations into global climate models as generalized INPBC parameterizations are not valid for diesel exhaust.

Radiative flux and forcing parameterization error in aerosol-free clear skies

DOE PAGES

Pincus, Robert; Mlawer, Eli J.; Oreopoulos, Lazaros; ...

2015-07-03

This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m 2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentiallymore » unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. As a result, a dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.« less

Two-moment bulk stratiform cloud microphysics in the GFDL AM3 GCM: description, evaluation, and sensitivity tests

NASA Astrophysics Data System (ADS)

Salzmann, M.; Ming, Y.; Golaz, J.-C.; Ginoux, P. A.; Morrison, H.; Gettelman, A.; Krämer, M.; Donner, L. J.

2010-08-01

A new stratiform cloud scheme including a two-moment bulk microphysics module, a cloud cover parameterization allowing ice supersaturation, and an ice nucleation parameterization has been implemented into the recently developed GFDL AM3 general circulation model (GCM) as part of an effort to treat aerosol-cloud-radiation interactions more realistically. Unlike the original scheme, the new scheme facilitates the study of cloud-ice-aerosol interactions via influences of dust and sulfate on ice nucleation. While liquid and cloud ice water path associated with stratiform clouds are similar for the new and the original scheme, column integrated droplet numbers and global frequency distributions (PDFs) of droplet effective radii differ significantly. This difference is in part due to a difference in the implementation of the Wegener-Bergeron-Findeisen (WBF) mechanism, which leads to a larger contribution from super-cooled droplets in the original scheme. Clouds are more likely to be either completely glaciated or liquid due to the WBF mechanism in the new scheme. Super-saturations over ice simulated with the new scheme are in qualitative agreement with observations, and PDFs of ice numbers and effective radii appear reasonable in the light of observations. Especially, the temperature dependence of ice numbers qualitatively agrees with in-situ observations. The global average long-wave cloud forcing decreases in comparison to the original scheme as expected when super-saturation over ice is allowed. Anthropogenic aerosols lead to a larger decrease in short-wave absorption (SWABS) in the new model setup, but outgoing long-wave radiation (OLR) decreases as well, so that the net effect of including anthropogenic aerosols on the net radiation at the top of the atmosphere (netradTOA = SWABS-OLR) is of similar magnitude for the new and the original scheme.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Two-moment bulk stratiform cloud microphysics in the GFDL AM3 GCM: description, evaluation, and sensitivity tests

NASA Astrophysics Data System (ADS)

Salzmann, M.; Ming, Y.; Golaz, J.-C.; Ginoux, P. A.; Morrison, H.; Gettelman, A.; Krämer, M.; Donner, L. J.

2010-03-01

A new stratiform cloud scheme including a two-moment bulk microphysics module, a cloud cover parameterization allowing ice supersaturation, and an ice nucleation parameterization has been implemented into the recently developed GFDL AM3 general circulation model (GCM) as part of an effort to treat aerosol-cloud-radiation interactions more realistically. Unlike the original scheme, the new scheme facilitates the study of cloud-ice-aerosol interactions via influences of dust and sulfate on ice nucleation. While liquid and cloud ice water path associated with stratiform clouds are similar for the new and the original scheme, column integrated droplet numbers and global frequency distributions (PDFs) of droplet effective radii differ significantly. This difference is in part due to a difference in the implementation of the Wegener-Bergeron-Findeisen (WBF) mechanism, which leads to a larger contribution from super-cooled droplets in the original scheme. Clouds are more likely to be either completely glaciated or liquid due to the WBF mechanism in the new scheme. Super-saturations over ice simulated with the new scheme are in qualitative agreement with observations, and PDFs of ice numbers and effective radii appear reasonable in the light of observations. Especially, the temperature dependence of ice numbers qualitatively agrees with in-situ observations. The global average long-wave cloud forcing decreases in comparison to the original scheme as expected when super-saturation over ice is allowed. Anthropogenic aerosols lead to a larger decrease in short-wave absorption (SWABS) in the new model setup, but outgoing long-wave radiation (OLR) decreases as well, so that the net effect of including anthropogenic aerosols on the net radiation at the top of the atmosphere (netradTOA = SWABS-OLR) is of similar magnitude for the new and the original scheme.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Parameterization of cloud glaciation by atmospheric dust

NASA Astrophysics Data System (ADS)

Nickovic, Slobodan; Cvetkovic, Bojan; Madonna, Fabio; Pejanovic, Goran; Petkovic, Slavko

2016-04-01

The exponential growth of research interest on ice nucleation (IN) is motivated, inter alias, by needs to improve generally unsatisfactory representation of cold cloud formation in atmospheric models, and therefore to increase the accuracy of weather and climate predictions, including better forecasting of precipitation. Research shows that mineral dust significantly contributes to cloud ice nucleation. Samples of residual particles in cloud ice crystals collected by aircraft measurements performed in the upper tropopause of regions distant from desert sources indicate that dust particles dominate over other known ice nuclei such as soot and biological particles. In the nucleation process, dust chemical aging had minor effects. The observational evidence on IN processes has substantially improved over the last decade and clearly shows that there is a significant correlation between IN concentrations and the concentrations of coarser aerosol at a given temperature and moisture. Most recently, due to recognition of the dominant role of dust as ice nuclei, parameterizations for immersion and deposition icing specifically due to dust have been developed. Based on these achievements, we have developed a real-time forecasting coupled atmosphere-dust modelling system capable to operationally predict occurrence of cold clouds generated by dust. We have been thoroughly validated model simulations against available remote sensing observations. We have used the CNR-IMAA Potenza lidar and cloud radar observations to explore the model capability to represent vertical features of the cloud and aerosol vertical profiles. We also utilized the MSG-SEVIRI and MODIS satellite data to examine the accuracy of the simulated horizontal distribution of cold clouds. Based on the obtained encouraging verification scores, operational experimental prediction of ice clouds nucleated by dust has been introduced in the Serbian Hydrometeorological Service as a public available product.

Incorporation of the planetary boundary layer in atmospheric models

NASA Technical Reports Server (NTRS)

Moeng, Chin-Hoh; Wyngaard, John; Pielke, Roger; Krueger, Steve

1993-01-01

The topics discussed include the following: perspectives on planetary boundary layer (PBL) measurements; current problems of PBL parameterization in mesoscale models; and convective cloud-PBL interactions.

EDITORIAL: Focus on Cloud Physics FOCUS ON CLOUD PHYSICS

NASA Astrophysics Data System (ADS)

Falkovich, Gregory; Malinowski, Szymon P.

2008-07-01

Cloud physics has for a long time been an important segment of atmospheric science. It is common knowledge that clouds are crucial for our understanding of weather and climate. Clouds are also interesting by themselves (not to mention that they are beautiful). Complexity is hidden behind the common picture of these beautiful and interesting objects. The typical school textbook definition that a cloud is 'a set of droplets or particles suspended in the atmosphere' is not adequate. Clouds are complicated phenomena in which dynamics, turbulence, microphysics, thermodynamics and radiative transfer interact on a wide range of scales, from sub-micron to kilometres. Some of these interactions are subtle and others are more straightforward. Large and small-scale motions lead to activation of cloud condensation nuclei, condensational growth and collisions; small changes in composition and concentration of atmospheric aerosol lead to significant differences in radiative properties of the clouds and influence rainfall formation. It is justified to look at a cloud as a composite, nonlinear system which involves many interactions and feedback. This system is actively linked into a web of atmospheric, oceanic and even cosmic interactions. Due to the complexity of the cloud system, present-day descriptions of clouds suffer from simplifications, inadequate parameterizations, and omissions. Sometimes the most fundamental physics hidden behind these simplifications and parameterizations is not known, and a wide scope of view can sometimes prevent a 'microscopic', deep insight into the detail. Only the expertise offered by scientists focused on particular elementary processes involved in this complicated pattern of interactions allows us to shape elements of the puzzle from which a general picture of clouds can be created. To be useful, every element of the puzzle must be shaped precisely. This often creates problems in communication between the sciences responsible for shaping elements of the puzzle, and those which combine them. Scales, assumptions and the conditions used in order to describe a particular single process of interest must be consistent with the conditions in clouds. The papers in this focus issue of New Journal of Physics collectively demonstrate (i) the variation in scientific approaches towards investigating cloud processes, (ii) the various stages of shaping elements of the puzzle, and (iii) some attempts to put the pieces together. These papers present just a small subset of loosely arranged elements in an initial stage of puzzle creation. Addressed by this issue is one of the important problems in our understanding of cloud processes—the interaction between cloud particles and turbulence. There is currently a gap between the cloud physics community and scientists working in wind tunnels, on turbulence theory and particle interactions. This collection is intended to narrow this gap by bringing together work by theoreticians, modelers, laboratory experimentalists and those who measure and observe actual processes in clouds. It forms a collage of contributions showing various approaches to cloud processes including: • theoretical works with possible applications to clouds (Bistagnino and Boffetta, Gustavsson et al), • an attempt to construct a phenomenological description of clouds and rain (Lovejoy and Schertzer), • simplified models designed to parameterize turbulence micro- and macro-effects (Celani et al, Derevyanko et al), • focused theoretical research aimed at particular cloud processes (Ayala et al, parts I and II, Wang et al), • laboratory and modeling studies of complex cloud processes (Malinowski et al). This collage is far from being complete but, hopefully, should give the reader a representative impression of the current state of knowledge in the field. We hope it will be useful to all scientists whose work is inspired by cloud processes. Focus on Cloud Physics Contents The equivalent size of cloud condensation nuclei Antonio Celani, Andrea Mazzino and Marco Tizzi Laboratory and modeling studies of cloud-clear air interfacial mixing: anisotropy of small-scale turbulence due to evaporative cooling Szymon P Malinowski, Miroslaw Andrejczuk, Wojciech W Grabowski, Piotr Korczyk, Tomasz A Kowalewski and Piotr K Smolarkiewicz Evolution of non-uniformly seeded warm clouds in idealized turbulent conditions Stanislav Derevyanko, Gregory Falkovich and Sergei Turitsyn Lagrangian statistics in two-dimensional free turbulent convection A Bistagnino and G Boffetta Turbulence, raindrops and the l1/2 number density law S Lovejoy and D Schertzer Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization Orlando Ayala, Bogdan Rosa and Lian-Ping Wang Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 1. Results from direct numerical simulation Orlando Ayala, Bogdan Rosa, Lian-Ping Wang and Wojciech W Grabowski Collisions of particles advected in random flows K Gustavsson, B Mehlig and M Wilkinson Turbulent collision efficiency of heavy particles relevant to cloud droplets Lian-Ping Wang, Orlando Ayala, Bogdan Rosa and Wojciech W Grabowski

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.

The GFS Atmospheric Model description

Science.gov Websites

model has only one type of cloud cover represented by C. In the tropics the cloudiness is primarily due mainly through grid-scale condensation. The fractional cloud cover C is available at all model levels , 1996: Parameterizations for the absorption of solar radiation by water vapor and ozone. J. Atmos. Sci

Site Scientist for the North Slope of Alaska Site

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

Verlinde, Johannes

2016-03-11

Under this grant our team contributed scientific support to the Department of Energy Atmospheric Radiation Program’s (DOE-ARM) Infrastructure team to maintain high quality research data at the DOE-ARM North Slope of Alaska with special emphasis on the radars. Under our guidance two major field campaigns focusing on mixed-phase Arctic clouds were conducted that greatly increased the community’s understanding of the many processes working together to control the evolution of single-layer cloud mixed-phase clouds. A series of modeling and observational studies revealed that the longevity of the radiatively important liquid phase is strongly dependent on how the ice phase develops inmore » mixed-phase clouds. A new ice microphysics parameterization was developed to capture better the natural evolution of ice particle growth in evolving environments. An ice particle scattering database was developed for all ARM radar frequencies. This database was used in a radar simulator (Doppler spectrum and polarimetric variables) to aid in the interpretation of the advanced ARM radars. At the conclusion of this project our team was poised to develop a complete radar simulator consistent with the new microphysical parameterization, taking advantage of parameterization’s advanced characterization of the ice shape and ice density.« less

A projected decrease in lightning under climate change

NASA Astrophysics Data System (ADS)

Finney, Declan L.; Doherty, Ruth M.; Wild, Oliver; Stevenson, David S.; MacKenzie, Ian A.; Blyth, Alan M.

2018-03-01

Lightning strongly influences atmospheric chemistry1-3, and impacts the frequency of natural wildfires4. Most previous studies project an increase in global lightning with climate change over the coming century1,5-7, but these typically use parameterizations of lightning that neglect cloud ice fluxes, a component generally considered to be fundamental to thunderstorm charging8. As such, the response of lightning to climate change is uncertain. Here, we compare lightning projections for 2100 using two parameterizations: the widely used cloud-top height (CTH) approach9, and a new upward cloud ice flux (IFLUX) approach10 that overcomes previous limitations. In contrast to the previously reported global increase in lightning based on CTH, we find a 15% decrease in total lightning flash rate with IFLUX in 2100 under a strong global warming scenario. Differences are largest in the tropics, where most lightning occurs, with implications for the estimation of future changes in tropospheric ozone and methane, as well as differences in their radiative forcings. These results suggest that lightning schemes more closely related to cloud ice and microphysical processes are needed to robustly estimate future changes in lightning and atmospheric composition.

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

Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.

Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce themore » bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.« less

Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea

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

Han, Ji-Young; Hong, Song-You; Sunny Lim, Kyo-Sun

The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversionmore » of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.« less

Diagnosing causes of cloud parameterization deficiencies using ARM measurements over SGP site

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

Wu, W.; Liu, Y.; Betts, A. K.

2010-03-15

Decade-long continuous surface-based measurements at Great Southern Plains (SGP) collected by the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility are first used to evaluate the three major reanalyses (i.e., ERA-Interim, NCEP/NCAR Reanalysis I and NCEP/DOE Reanalysis II) to identify model biases in simulating surface shortwave cloud forcing and total cloud fraction. The results show large systematic lower biases in the modeled surface shortwave cloud forcing and cloud fraction from all the three reanalysis datasets. Then we focus on diagnosing the causes of these model biases using the Active Remote Sensing of Clouds (ARSCL) products (e.g., verticalmore » distribution of cloud fraction, cloud-base and cloud-top heights, and cloud optical depth) and meteorological measurements (temperature, humidity and stability). Efforts are made to couple cloud properties with boundary processes in the diagnosis.« less

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

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

McFarquhar, Greg

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

Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

NASA Technical Reports Server (NTRS)

Cahalan, R. F.; Morcrette, J. J.

1999-01-01

Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.

Normalized Implicit Radial Models for Scattered Point Cloud Data without Normal Vectors

DTIC Science & Technology

2009-03-23

points by shrinking a discrete membrane, Computer Graphics Forum, Vol. 24-4, 2005, pp. 791-808 [8] Floater , M. S., Reimers, M.: Meshless...Parameterization and Surface Reconstruction, Computer Aided Geometric Design 18, 2001, pp 77-92 [9] Floater , M. S.: Parameterization of Triangulations and...Unorganized Points, In: Tutorials on Multiresolution in Geometric Modelling, A. Iske, E. Quak and M. S. Floater (eds.), Springer , 2002, pp. 287-316 [10

Sea breeze: Induced mesoscale systems and severe weather

NASA Technical Reports Server (NTRS)

Nicholls, M. E.; Pielke, R. A.; Cotton, W. R.

1990-01-01

Sea-breeze-deep convective interactions over the Florida peninsula were investigated using a cloud/mesoscale numerical model. The objective was to gain a better understanding of sea-breeze and deep convective interactions over the Florida peninsula using a high resolution convectively explicit model and to use these results to evaluate convective parameterization schemes. A 3-D numerical investigation of Florida convection was completed. The Kuo and Fritsch-Chappell parameterization schemes are summarized and evaluated.

Processing Doppler Lidar and Cloud Radar Observations for Analysis of Convective Mass Flux Parameterizations Using DYNAMO Direct Observations

DTIC Science & Technology

2014-09-30

for Analysis of Convective Mass Flux Parameterizations Using DYNAMO Direct Observations R. Michael Hardesty CIRES/University of Colorado/NOAA 325...the RV-Revell during legs 2 & 3 of the DYNAMO experiement to help characterize vertical transport through the boundary layer and to build statistics...obtained during DYNAMO , and to investigate whether cold pools that emanate from convection organize the interplay between humidity and convection and

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

DOE PAGES

Yang, Fan; Luke, Edward P.; Kollias, Pavlos; ...

2018-04-20

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

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

Yang, Fan; Luke, Edward P.; Kollias, Pavlos

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Shortwave flux at the surface of the Atlantic Ocean: in-situ measurements, satellite data and parametrization.

NASA Astrophysics Data System (ADS)

Sinitsyn, Alexey

2017-04-01

Shortwave radiation is one of the key air-sea flux components playing an important role in on the ocean heat balance. The most accurate method to obtaining estimates of shortwave fluxes are the field measurements at various locations at the globe. However, these data are very sparse. Different satellite missions and re-analyses provide alternative source of short-wave radiation data, however they need are source for uncertainties and need to be validated. An alternative way to produce long-term time series of shortwave radiation is to apply bulk parameterizations of shortwave radiation to the observations of Voluntary Observing Ship (VOS) cloud data or to the cloud measurements from CM-SAF. In our work, we compare three sources of shortwave flux estimates. In-situ measurements were obtained during 12 cruises (320 day of measurements) of research cruises in different regions of the Atlantic Ocean from 2004 to 2014. Shortwave radiation was measured by the Kipp&Zonen net radiometer CNR-1. Also during the cruise, standard meteorological observations were carried out. Satellite data were the hourly and daily time series of the incoming shortwave radiation with spatial resolution 0.05x0.05 degree (METEOSAT MSG coverage Europe, Africa, Atlantic Ocean), and were obtained by the MVIRI/SEVIRI instrument from METEOSAT. SEVIRI cloud properties were taken from CLAAS-2 data record from CM-SAF. Parameterizations of shortwave fluxes used consisted of three different schemes based upon consideration of only total as well as total and low cloud cover. The incoming shortwave radiation retrieved by satellite had a positive bias of 3 Wm-2 and RMS of 69 Wm-2 compared to in-situ measurements. For different Octa categories the bias was from 1 to 5 Wm-2 and RMS from 41 to 71 Wm-2. The incoming shortwave radiation computed by bulk parameterization indicated a bias of -10 Wm-2 to 60 Wm-2 depending on the scheme and the region of the Atlantic Ocean. The results of the comparison suggest that satellite data is an excellent ground for testing bulk parameterizations of incoming shortwave radiation. Among the bulk paramterizations, the IORAS/SAIL scheme is the least biased algorithm for computing shortwave radiation from cloud observations.

The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics

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

Gustafson, William I.; Ma, Po-Lun; Xiao, Heng

2013-08-29

The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependencemore » of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.« less

Impact of Aerosol Processing on Orographic Clouds

NASA Astrophysics Data System (ADS)

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

2010-05-01

Aerosol particles undergo significant modifications during their residence time in the atmosphere. Physical processes like coagulation, coating and water uptake, and aqueous surface chemistry alter the aerosol size distribution and composition. At this, clouds play a primary role as physical and chemical processing inside cloud droplets contributes considerably to the changes in aerosol particles. A previous study estimates that on global average atmospheric particles are cycled three times through a cloud before being removed from the atmosphere [1]. An explicit and detailed treatment of cloud-borne particles has been implemented in the regional weather forecast and climate model COSMO-CLM. The employed model version includes a two-moment cloud microphysical scheme [2] that has been coupled to the aerosol microphysical scheme M7 [3] as described by Muhlbauer and Lohmann, 2008 [4]. So far, the formation, transfer and removal of cloud-borne aerosol number and mass were not considered in the model. Following the parameterization for cloud-borne particles developed by Hoose et al., 2008 [5], distinction between in-droplet and in-crystal particles is made to more physically account for processes in mixed-phase clouds, such as the Wegener-Bergeron-Findeisen process and contact and immersion freezing. In our model, this approach has been extended to allow for aerosol particles in five different hydrometeors: cloud droplets, rain drops, ice crystals, snow flakes and graupel. We account for nucleation scavenging, freezing and melting processes, autoconversion, accretion, aggregation, riming and selfcollection, collisions between interstitial aerosol particles and hydrometeors, ice multiplication, sedimentation, evaporation and sublimation. The new scheme allows an evaluation of the cloud cycling of aerosol particles by tracking the particles even when scavenged into hydrometeors. Global simulations of aerosol processing in clouds have recently been conducted by Hoose et al. [6]. Our investigation regarding the influence of aerosol processing will focus on the regional scale using a cloud-system resolving model with a much higher resolution. Emphasis will be placed on orographic mixed-phase precipitation. Different two-dimensional simulations of idealized orographic clouds will be conducted to estimate the effect of aerosol processing on orographic cloud formation and precipitation. Here, cloud lifetime, location and extent as well as the cloud type will be of particular interest. In a supplementary study, the new parameterization will be compared to observations of total and interstitial aerosol concentrations and size distribution at the remote high alpine research station Jungfraujoch in Switzerland. In addition, our simulations will be compared to recent simulations of aerosol processing in warm, mixed-phase and cold clouds, which have been carried out at the location of Jungfraujoch station [5]. References: [1] Pruppacher & Jaenicke (1995), The processing of water vapor and aerosols by atmospheric clouds, a global estimate, Atmos. Res., 38, 283295. [2] Seifert & Beheng (2006), A two-moment microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 4566. [3] Vignati et al. (2004), An efficient size-resolved aerosol microphysics module for large-scale transport models, J. Geophys. Res., 109, D22202 [4] Muhlbauer & Lohmann (2008), Sensitivity studies of the role of aerosols in warm-phase orographic precipitation in different flow regimes, J. Atmos. Sci., 65, 25222542. [5] Hoose et al. (2008), Aerosol processing in mixed-phase clouds in ECHAM5HAM: Model description and comparison to observations, J. Geophys. Res., 113, D071210. [6] Hoose et al. (2008), Global simulations of aerosol processing in clouds, Atmos. Chem. Phys., 8, 69396963.

A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.

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

Luke,E.; Kollias, P.

2007-08-06

The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less

Sensitivity of Homogeneous Ice Nucleation to Aerosol Perturbations and Its Implications for Aerosol Indirect Effects Through Cirrus Clouds

NASA Astrophysics Data System (ADS)

Liu, X.; Shi, X.

2018-02-01

The magnitude and sign of anthropogenic aerosol impacts on cirrus clouds through ice nucleation are still very uncertain. In this study, aerosol sensitivity (ηα), defined as the sensitivity of the number concentration (Ni) of ice crystals formed from homogeneous ice nucleation to aerosol number concentration (Na), is examined based on simulations from a cloud parcel model. The model represents the fundamental process of ice crystal formation that results from homogeneous nucleation. We find that the geometric dispersion (σ) of the aerosol size distribution used in the model is a key factor for ηα. For a monodisperse size distribution, ηα is close to zero in vertical updrafts (V < 50 cm s-1) typical of cirrus clouds. However, ηα increases to 0.1-0.3 (i.e., Ni increases by a factor of 1.3-2.0 for a tenfold increase in Na) if aerosol particles follow lognormal size distributions with a σ of 1.6-2.3 in the upper troposphere. By varying the input aerosol and environmental parameters, our model reproduces a large range of ηα values derived from homogeneous ice nucleation parameterizations widely used in global climate models (GCMs). The differences in ηα from these parameterizations can translate into a range of anthropogenic aerosol longwave indirect forcings through cirrus clouds from 0.05 to 0.36 W m-2 with a GCM. Our study suggests that a larger ηα (0.1-0.3) is more plausible and the homogeneous nucleation parameterizations should include a realistic aerosol size distribution to accurately quantify anthropogenic aerosol indirect effects.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Investigating the scale-adaptivity of a shallow cumulus parameterization scheme with LES

NASA Astrophysics Data System (ADS)

Brast, Maren; Schemann, Vera; Neggers, Roel

2017-04-01

In this study we investigate the scale-adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone. The Eddy-Diffusivity Multiple Mass-Flux (or ED(MF)n ) scheme is a bin-macrophysics scheme, in which subgrid transport is formulated in terms of discretized size densities. While scale-adaptivity in the ED-component is achieved using a pragmatic blending approach, the MF-component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented in a large-eddy simulation (LES) model, replacing the original subgrid-scheme for turbulent transport. LES thus plays the role of a non-hydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary-layer gray zone. In this range convective cumulus clouds are partially resolved. We find that at high resolutions the clouds and the turbulent transport are predominantly resolved by the LES, and the transport represented by ED(MF)n is small. This partitioning changes towards coarser resolutions, with the representation of shallow cumulus clouds becoming exclusively carried by the ED(MF)n. The way the partitioning changes with grid-spacing matches the results of previous LES studies, suggesting some scale-adaptivity is captured. Sensitivity studies show that a scale-inadaptive ED component stays too active at high resolutions, and that the results are fairly insensitive to the number of transporting updrafts in the ED(MF)n scheme. Other assumptions in the scheme, such as the distribution of updrafts across sizes and the value of the area fraction covered by updrafts, are found to affect the location of the gray zone.

Extended field observations of cirrus clouds using a ground-based cloud observing system

NASA Technical Reports Server (NTRS)

Ackerman, Thomas P.

1994-01-01

The evolution of synoptic-scale dynamics associated with a middle and upper tropospheric cloud event that occurred on 26 November 1991 is examined. The case under consideration occurred during the FIRE CIRRUS-II Intensive Field Observing Period held in Coffeyville, KS during Nov. and Dec., 1991. Using data from the wind profiler demonstration network and a temporally and spatially augmented radiosonde array, emphasis is given to explaining the evolution of the kinematically-derived ageostrophic vertical circulations and correlating the circulation with the forcing of an extensively sampled cloud field. This is facilitated by decomposing the horizontal divergence into its component parts through a natural coordinate representation of the flow. Ageostrophic vertical circulations are inferred and compared to the circulation forcing arising from geostrophic confluence and shearing deformation derived from the Sawyer-Eliassen Equation. It is found that a thermodynamically indirect vertical circulation existed in association with a jet streak exit region. The circulation was displaced to the cyclonic side of the jet axis due to the orientation of the jet exit between a deepening diffluent trough and building ridge. The cloud line formed in the ascending branch of the vertical circulation with the most concentrated cloud development occurring in conjunction with the maximum large-scale vertical motion. The relationship between the large scale dynamics and the parameterization of middle and upper tropospheric clouds in large-scale models is discussed and an example of ice water contents derived from a parameterization forced by the diagnosed vertical motions and observed water vapor contents is presented.

Parameterization of cloud lidar backscattering profiles by means of asymmetrical Gaussians

NASA Astrophysics Data System (ADS)

del Guasta, Massimo; Morandi, Marco; Stefanutti, Leopoldo

1995-06-01

A fitting procedure for cloud lidar data processing is shown that is based on the computation of the first three moments of the vertical-backscattering (or -extinction) profile. Single-peak clouds or single cloud layers are approximated to asymmetrical Gaussians. The algorithm is particularly stable with respect to noise and processing errors, and it is much faster than the equivalent least-squares approach. Multilayer clouds can easily be treated as a sum of single asymmetrical Gaussian peaks. The method is suitable for cloud-shape parametrization in noisy lidar signatures (like those expected from satellite lidars). It also permits an improvement of cloud radiative-property computations that are based on huge lidar data sets for which storage and careful examination of single lidar profiles can't be carried out.

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

PubMed

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

2017-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

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

The Incorporation and Initialization of Cloud Water/ice in AN Operational Forecast Model

NASA Astrophysics Data System (ADS)

Zhao, Qingyun

Quantitative precipitation forecasts have been one of the weakest aspects of numerical weather prediction models. Theoretical studies show that the errors in precipitation calculation can arise from three sources: errors in the large-scale forecasts of primary variables, errors in the crude treatment of condensation/evaporation and precipitation processes, and errors in the model initial conditions. A new precipitation parameterization scheme has been developed to investigate the forecast value of improved precipitation physics via the introduction of cloud water and cloud ice into a numerical prediction model. The main feature of this scheme is the explicit calculation of cloud water and cloud ice in both the convective and stratiform precipitation parameterization. This scheme has been applied to the eta model at the National Meteorological Center. Four extensive tests have been performed. The statistical results showed a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly. Since three-dimensional cloud data is absent from the analysis/assimilation system for most numerical models, a method has been proposed to incorporate observed precipitation and nephanalysis data into the data assimilation system to obtain the initial cloud field for the eta model. In this scheme, the initial moisture and vertical motion fields are also improved at the same time as cloud initialization. The physical initialization is performed in a dynamical initialization framework that uses the Newtonian dynamical relaxation method to nudge the model's wind and mass fields toward analyses during a 12-hour data assimilation period. Results from a case study showed that a realistic cloud field was produced by this method at the end of the data assimilation period. Precipitation forecasts have been significantly improved as a result of the improved initial cloud, moisture and vertical motion fields.

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

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

Sensitivity of simulated snow cloud properties to mass-diameter parameterizations.

NASA Astrophysics Data System (ADS)

Duffy, G.; Nesbitt, S. W.; McFarquhar, G. M.

2015-12-01

Mass to diameter (m-D) relationships are used in model parameterization schemes to represent ice cloud microphysics and in retrievals of bulk cloud properties from remote sensing instruments. One of the most common relationships, used in the current Global Precipitation Measurement retrieval algorithm for example, assigns the density of snow as a constant tenth of the density of ice (0.1g/m^3). This assumption stands in contrast to the results of derived m-D relationships of snow particles, which imply decreasing particle densities at larger sizes and result in particle masses orders of magnitude below the constant density relationship. In this study, forward simulations of bulk cloud properties (e.g., total water content, radar reflectivity and precipitation rate) derived from measured size distributions using several historical m-D relationships are presented. This expands upon previous studies that mainly focused on smaller ice particles because of the examination of precipitation-sized particles here. In situ and remote sensing data from the GPM Cold season Experiment (GCPEx) and Canadian CloudSAT/Calypso Validation Program (C3VP), both synoptic snowstorm field experiments in southern Ontario, Canada, are used to evaluate the forward simulations against total water content measured by the Nevzorov and Cloud Spectrometer and Impactor (CSI) probe, radar reflectivity measured by a C band ground based radar and a nadir pointing Ku/Ka dual frequency airborne radar, and precipitation rate measured by a 2D video disdrometer. There are differences between the bulk cloud properties derived using varying m-D relations, with constant density assumptions producing results differing substantially from the bulk measured quantities. The variability in bulk cloud properties derived using different m-D relations is compared against the natural variability in those parameters seen in the GCPEx and C3VP field experiments.

A Parameterization for Land-Atmosphere-Cloud Exchange (PLACE): Documentation and Testing of a Detailed Process Model of the Partly Cloudy Boundary Layer over Heterogeneous Land.

NASA Astrophysics Data System (ADS)

Wetzel, Peter J.; Boone, Aaron

1995-07-01

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

Study of the Evolution of the Electric Structure of a Convective Cloud Using the Data of a Numerical Nonstationary Three-Dimensional Model

NASA Astrophysics Data System (ADS)

Veremey, N. E.; Dovgalyuk, Yu. A.; Zatevakhin, M. A.; Ignatyev, A. A.; Morozov, V. N.

2014-04-01

Numerical nonstationary three-dimensional model of a convective cloud with parameterized description of microphysical processes with allowance for the electrization processes is considered. The results of numerical modeling of the cloud evolution for the specified atmospheric conditions are presented. The spatio-temporal distribution of the main cloud characteristics including the volume charge density and the electric field is obtained. The calculation results show that the electric structure of the cloud is different at its various life stages, i.e., it varies from unipolar to dipolar and then to tripolar. This conclusion is in fair agreement with the field studies.

Technical Report Series on Global Modeling and Data Assimilation. Volume 20; The Climate of the FVCCM-3 Model

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Yehui; Schubert, Siegfried D.; Lin, Shian-Jiann; Nebuda, Sharon; Shen, Bo-Wen

2001-01-01

This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing.

Surface Net Solar Radiation Estimated from Satellite Measurements: Comparisons with Tower Observations

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Leighton, H. G.; Cess, Robert D.

1993-01-01

A parameterization that relates the reflected solar flux at the top of the atmosphere to the net solar flux at the surface in terms of only the column water vapor amount and the solar zenith angle was tested against surface observations. Net surface fluxes deduced from coincidental collocated satellite-measured radiances and from measurements from towers in Boulder during summer and near Saskatoon in winter have mean differences of about 2 W/sq m, regardless of whether the sky is clear or cloudy. Furthermore, comparisons between the net fluxes deduced from the parameterization and from surface measurements showed equally good agreement when the data were partitioned into morning and afternoon observations. This is in contrast to results from an empirical clear-sky algorithm that is unable to account adequately for the effects of clouds and that shows, at Boulder, a distinct morning to afternoon variation, which is presumably due to the predominance of different cloud types throughout the day. It is also demonstrated that the parameterization may be applied to irradiances at the top of the atmosphere that have been temporally averaged by using the temporally averaged column water vapor amount and the temporally averaged cosine of the solar zenith angle. The good agreement between the results of the parameterization and surface measurements suggests that the algorithm is a useful tool for a variety of climate studies.

GHI calculation sensitivity on microphysics, land- and cumulus parameterization in WRF over the Reunion Island

NASA Astrophysics Data System (ADS)

De Meij, A.; Vinuesa, J.-F.; Maupas, V.

2018-05-01

The sensitivity of different microphysics and dynamics schemes on calculated global horizontal irradiation (GHI) values in the Weather Research Forecasting (WRF) model is studied. 13 sensitivity simulations were performed for which the microphysics, cumulus parameterization schemes and land surface models were changed. Firstly we evaluated the model's performance by comparing calculated GHI values for the Base Case with observations for the Reunion Island for 2014. In general, the model calculates the largest bias during the austral summer. This indicates that the model is less accurate in timing the formation and dissipation of clouds during the summer, when higher water vapor quantities are present in the atmosphere than during the austral winter. Secondly, the model sensitivity on changing the microphysics, cumulus parameterization and land surface models on calculated GHI values is evaluated. The sensitivity simulations showed that changing the microphysics from the Thompson scheme (or Single-Moment 6-class scheme) to the Morrison double-moment scheme, the relative bias improves from 45% to 10%. The underlying reason for this improvement is that the Morrison double-moment scheme predicts the mass and number concentrations of five hydrometeors, which help to improve the calculation of the densities, size and lifetime of the cloud droplets. While the single moment schemes only predicts the mass for less hydrometeors. Changing the cumulus parameterization schemes and land surface models does not have a large impact on GHI calculations.

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

NASA Astrophysics Data System (ADS)

Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

2016-05-01

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

The parameterization of the planetary boundary layer in the UCLA general circulation model - Formulation and results

NASA Technical Reports Server (NTRS)

Suarez, M. J.; Arakawa, A.; Randall, D. A.

1983-01-01

A planetary boundary layer (PBL) parameterization for general circulation models (GCMs) is presented. It uses a mixed-layer approach in which the PBL is assumed to be capped by discontinuities in the mean vertical profiles. Both clear and cloud-topped boundary layers are parameterized. Particular emphasis is placed on the formulation of the coupling between the PBL and both the free atmosphere and cumulus convection. For this purpose a modified sigma-coordinate is introduced in which the PBL top and the lower boundary are both coordinate surfaces. The use of a bulk PBL formulation with this coordinate is extensively discussed. Results are presented from a July simulation produced by the UCLA GCM. PBL-related variables are shown, to illustrate the various regimes the parameterization is capable of simulating.

Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Yu, Ruyi; Molthan, Andrew L.; Nesbitt, Steven

2014-01-01

It is hypothesized microphysical predictions have greater uncertainties/errors when there are complex interactions that result from mixed phased processes like riming. Use Global Precipitation Measurement (GPM) Mission ground validation studies in Ontario, Canada to verify and improve parameterizations. The WRF realistically simulated the warm frontal snowband at relatively short lead times (1014 h). The snowband structire is sensitive to the microphysical parameterization used in WRF. The Goddard and SBUYLin most realistically predicted the band structure, but overpredicted snow content. The double moment Morrison scheme best produced the slope of the snow distribution, but it underpredicted the intercept. All schemes and the radar derived (which used dry snow ZR) underpredicted the surface precipitation amount, likely because there was more cloud water than expected. The Morrison had the most cloud water and the best precipitation prediction of all schemes.

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

Predicting Decade-to-Century Climate Change: Prospects for Improving Models

NASA Technical Reports Server (NTRS)

Somerville, Richard C. J.

1999-01-01

Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations.

Assimilation of Satellite Data in Regional Air Quality Models

NASA Technical Reports Server (NTRS)

Mcnider, Richard T.; Norris, William B.; Casey, Daniel; Pleim, Jonathan E.; Roselle, Shawn J.; Lapenta, William M.

1997-01-01

In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry.

Contrails and their impact on shortwave radiation and photovoltaic power production - a regional model study

NASA Astrophysics Data System (ADS)

Gruber, Simon; Unterstrasser, Simon; Bechtold, Jan; Vogel, Heike; Jung, Martin; Pak, Henry; Vogel, Bernhard

2018-05-01

A high-resolution regional-scale numerical model was extended by a parameterization that allows for both the generation and the life cycle of contrails and contrail cirrus to be calculated. The life cycle of contrails and contrail cirrus is described by a two-moment cloud microphysical scheme that was extended by a separate contrail ice class for a better representation of the high concentration of small ice crystals that occur in contrails. The basic input data set contains the spatially and temporally highly resolved flight trajectories over Central Europe derived from real-time data. The parameterization provides aircraft-dependent source terms for contrail ice mass and number. A case study was performed to investigate the influence of contrails and contrail cirrus on the shortwave radiative fluxes at the earth's surface. Accounting for contrails produced by aircraft enabled the model to simulate high clouds that were otherwise missing on this day. The effect of these extra clouds was to reduce the incoming shortwave radiation at the surface as well as the production of photovoltaic power by up to 10 %.

A Multi-Model Analysis of the Cloud Phase Transition in 16 GCMs Using Satellite Observations (CALIPSO/GPCP) and Reanalysis Data (ECMWF/MERRA).

NASA Astrophysics Data System (ADS)

Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J. L. F.

2014-12-01

The ubiquitous presence of clouds within the troposphere contributes to modulate the radiative balance of the earth-atmosphere system. Depending on their cloud phase, clouds may have different microphysical and macrophysical properties, and hence, different radiative effects. In this study, we took advantage of climate runs from the GASS-YoTC and AMIP multi-model experiments to document the differences associated to the cloud phase parameterizations of 16 GCMs. A particular emphasize has been put on the vertical structure of the transition between liquid and ice in clouds. A way to intercompare the models regardless of their cloud fraction is to study the ratio of the ice mass to the total mass of the condensed water. To address the challenge of evaluating the modeled cloud phase, we profited from the cloud phase climatology so called CALIPSO-GOCCP, which separates liquid clouds from ice clouds at global scale, with a high vertical resolution (480m), above all surfaces. We also used reanalysis data and GPCP satellite observations to investigate the influence of the temperature, the relative humidity, the vertical wind speed and the precipitations on the cloud phase transition. In 12 (of 16) models, there are too few super cooled liquid in clouds compared to observations, mostly in the high troposphere. We exhibited evidences of the link between the cloud phase transition and the humidity, the vertical wind speed as well as the precipitations. Some cloud phase schemes are more affected by the humidity and the vertical velocity and some other by the precipitations. Although a few models can reproduce the observe relation between cloud phase and temperature, humidity, vertical velocity or precipitations, none of them perform well for all the parameters. An important result of this study is that the T-dependent phase parameterizations do not allow simulating the complexity of the observed cloud phase transition. Unfortunately, more complex microphysics schemes do not succeed to reproduce all the processes neither. Finally, thanks to the combined use of CALIPSO-GOCCP and ECMWF water vapor pressure, we showed an updated version of the Clausius-Clapeyron water vapor phase diagram. This diagram represents a new tool to improve the simulation of the cloud phase transition in climate models.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Development of Two-Moment Cloud Microphysics for Liquid and Ice Within the NASA Goddard Earth Observing System Model (GEOS-5)

NASA Technical Reports Server (NTRS)

Barahona, Donifan; Molod, Andrea M.; Bacmeister, Julio; Nenes, Athanasios; Gettelman, Andrew; Morrison, Hugh; Phillips, Vaughan,; Eichmann, Andrew F.

2013-01-01

This work presents the development of a two-moment cloud microphysics scheme within the version 5 of the NASA Goddard Earth Observing System (GEOS-5). The scheme includes the implementation of a comprehensive stratiform microphysics module, a new cloud coverage scheme that allows ice supersaturation and a new microphysics module embedded within the moist convection parameterization of GEOS-5. Comprehensive physically-based descriptions of ice nucleation, including homogeneous and heterogeneous freezing, and liquid droplet activation are implemented to describe the formation of cloud particles in stratiform clouds and convective cumulus. The effect of preexisting ice crystals on the formation of cirrus clouds is also accounted for. A new parameterization of the subgrid scale vertical velocity distribution accounting for turbulence and gravity wave motion is developed. The implementation of the new microphysics significantly improves the representation of liquid water and ice in GEOS-5. Evaluation of the model shows agreement of the simulated droplet and ice crystal effective and volumetric radius with satellite retrievals and in situ observations. The simulated global distribution of supersaturation is also in agreement with observations. It was found that when using the new microphysics the fraction of condensate that remains as liquid follows a sigmoidal increase with temperature which differs from the linear increase assumed in most models and is in better agreement with available observations. The performance of the new microphysics in reproducing the observed total cloud fraction, longwave and shortwave cloud forcing, and total precipitation is similar to the operational version of GEOS-5 and in agreement with satellite retrievals. However the new microphysics tends to underestimate the coverage of persistent low level stratocumulus. Sensitivity studies showed that the simulated cloud properties are robust to moderate variation in cloud microphysical parameters. However significant sensitivity in ice cloud properties was found to variation in the dispersion of the ice crystal size distribution and the critical size for ice autoconversion. The implementation of the new microphysics leads to a more realistic representation of cloud processes in GEOS-5 and allows the linkage of cloud properties to aerosol emissions.

Determination of cloud parameters from infrared sounder data

NASA Technical Reports Server (NTRS)

Yeh, H.-Y. M.

1984-01-01

The World Climate Research Programme (WCRP) plan is concerned with the need to develop a uniform global cloud climatology as part of a broad research program on climate processes. The International Satellite Cloud Climatology Project (ISCCP) has been approved as the first project of the WCRP. The ISCCP has the basic objective to collect and analyze satellite radiance data to infer the global distribution of cloud radiative properties in order to improve the modeling of cloud effects on climate. Research is conducted to explore an algorithm for retrieving cloud properties by utilizing the available infrared sounder data from polar-orbiting satellites. A numerical method is developed for computing cloud top heights, amount, and emissivity on the basis of a parameterized infrared radiative transfer equation for cloudy atmospheres. Theoretical studies were carried out by considering a synthetic atmosphere.

An experimental investigation of the angular scattering and backscattering behaviors of the simulated clouds of the outer planets

NASA Technical Reports Server (NTRS)

Sassen, K.

1984-01-01

A cryogenic, 50 liter volume Planetary Cloud Simulation Chamber has been constructed to permit the laboratory study of the cloud compositions which are likely to be found in the atmospheres of the outer planets. On the basis of available data, clouds composed of water ice, carbon dioxide, and liquid and solid ammonia and methane, both pure and in various mixtures, have been generated. Cloud microphysical observations have been permitted through the use of a cloud particle slide injector and photomicrography. Viewports in the lower chamber have enabled the collection of cloud backscattering data using 633 and 838 nm laser light, including linear depolarization ratios and complete Stokes parameterization. The considerable technological difficulties associated with the collection of angular scattering patterns within the chamber, however, could not be completely overcome.

Integrated approach towards understanding interactions of mineral dust aerosol with warm clouds

NASA Astrophysics Data System (ADS)

Kumar, Prashant

2011-12-01

Mineral dust is ubiquitous in the atmosphere and represents a dominant type of particulate matter by mass. Dust particles can serve as cloud condensation nuclei (CCN), giant CCN (GCCN), or ice nuclei (IN), thereby, affecting cloud microphysics, albedo, and lifetime. Despite its well-recognized importance, assessments of dust impacts on clouds and climate remain highly uncertain. This thesis addresses the role of dust as CCN and GCCN with the goal of improving our understanding of dust-warm cloud interactions and their representation in climate models. Most studies to date focus on the soluble fraction of aerosol particles when describing cloud droplet nucleation, and overlook the interactions of the hydrophilic insoluble fraction with water vapor. A new approach to include such interactions (expressed by the process of water vapor adsorption) is explored, by combining multilayer Frenkel-Halsey-Hill (FHH) physical adsorption isotherm and curvature (Kelvin) effects. The importance of adsorption activation theory (FHH-AT) is corroborated by measurements of CCN activity of mineral aerosols generated from clays, calcite, quartz, and desert soil samples from Northern Africa, East Asia/China, and Northern America. A new aerosol generation setup for CCN measurements was developed based on a dry generation technique capable of reproducing natural dust aerosol emission. Based on the dependence of critical supersaturation with particle dry diameter, it is found that the FHH-AT is a better framework for describing fresh (and unprocessed) dust CCN activity than the classical Kohler theory (KT). Ion Chromatography (IC) measurements performed on fresh regional dust samples indicate negligible soluble fraction, and support that water vapor adsorption is the prime source of CCN activity in the dust. CCN measurements with the commonly used wet generated mineral aerosol (from atomization of a dust aqueous suspension) are also carried out. Results indicate that the method is subject to biases as it generates a bimodal size distribution with a broad range of hygroscopicity. It is found that smaller particles generated in the more hygroscopic peak follow CCN activation by KT, while the larger peak is less hydrophilic with activation similar to dry generated dust that follow FHH-AT. Droplet activation kinetics measurements demonstrate that dry generated mineral aerosol display retarded activation kinetics with an equivalent water vapor uptake coefficient that is 30 - 80% lower relative to ammonium sulfate aerosol. Wet generated mineral aerosols, however, display similar activation kinetics to ammonium sulfate. These results suggest that at least a monolayer of water vapor (the rate-limiting step for adsorption) persists during the timescale of aerosol generation in the experiment, and questions the atmospheric relevance of studies on mineral aerosol generated from wet atomization method. A new parameterization of cloud droplet formation from insoluble dust CCN for regional and global climate models is also developed. The parameterization framework considers cloud droplet formation from dust CCN activating via FHH-AT, and soluble aerosol with activation described through KT. The parameterization is validated against a numerical parcel model, agreeing with predictions to within 10% (R2 ˜ 0.98). The potential role of dust GCCN activating by FHH-AT within warm stratocumulus and convective clouds is also evaluated. It is found that under pristine aerosol conditions, dust GCCN can act as collector drops with implications to dust-cloud-precipitation linkages. Biases introduced from describing dust GCCN activation by KT are also addressed. The results demonstrate that dust particles do not require deliquescent material to act as CCN in the atmosphere. Furthermore, the impact of dust particles as giant CCN on warm cloud and precipitation must be considered. Finally, the new parameterization of cloud droplet formation can be implemented in regional and global models providing an improved treatment of mineral aerosol on clouds and precipitation. The new framework is uniquely placed to address dust aerosol indirect effects on climate.

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.

The effect of clouds on the earth's radiation budget

NASA Technical Reports Server (NTRS)

Ziskin, Daniel; Strobel, Darrell F.

1991-01-01

The radiative fluxes from the Earth Radiation Budget Experiment (ERBE) and the cloud properties from the International Satellite Cloud Climatology Project (ISCCP) over Indonesia for the months of June and July of 1985 and 1986 were analyzed to determine the cloud sensitivity coefficients. The method involved a linear least squares regression between co-incident flux and cloud coverage measurements. The calculated slope is identified as the cloud sensitivity. It was found that the correlations between the total cloud fraction and radiation parameters were modest. However, correlations between cloud fraction and IR flux were improved by separating clouds by height. Likewise, correlations between the visible flux and cloud fractions were improved by distinguishing clouds based on optical depth. Calculating correlations between the net fluxes and either height or optical depth segregated cloud fractions were somewhat improved. When clouds were classified in terms of their height and optical depth, correlations among all the radiation components were improved. Mean cloud sensitivities based on the regression of radiative fluxes against height and optical depth separated cloud types are presented. Results are compared to a one-dimensional radiation model with a simple cloud parameterization scheme.

Impact of capturing rainfall scavenging intermittency using cloud superparameterization on simulated continental scale wildfire smoke transport

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.

2011-12-01

Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.

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

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

2005-01-01

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

An empirical test of a diffusion model: predicting clouded apollo movements in a novel environment.

PubMed

Ovaskainen, Otso; Luoto, Miska; Ikonen, Iiro; Rekola, Hanna; Meyke, Evgeniy; Kuussaari, Mikko

2008-05-01

Functional connectivity is a fundamental concept in conservation biology because it sets the level of migration and gene flow among local populations. However, functional connectivity is difficult to measure, largely because it is hard to acquire and analyze movement data from heterogeneous landscapes. Here we apply a Bayesian state-space framework to parameterize a diffusion-based movement model using capture-recapture data on the endangered clouded apollo butterfly. We test whether the model is able to disentangle the inherent movement behavior of the species from landscape structure and sampling artifacts, which is a necessity if the model is to be used to examine how movements depend on landscape structure. We show that this is the case by demonstrating that the model, parameterized with data from a reference landscape, correctly predicts movements in a structurally different landscape. In particular, the model helps to explain why a movement corridor that was constructed as a management measure failed to increase movement among local populations. We illustrate how the parameterized model can be used to derive biologically relevant measures of functional connectivity, thus linking movement data with models of spatial population dynamics.

GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems (WG2)

NASA Technical Reports Server (NTRS)

Starr, David

2002-01-01

Status, progress and plans will be given for current GCSS (GEWEX Cloud System Study) WG2 (Working Group on Cirrus Cloud Systems) projects, including: (a) the Idealized Cirrus Model Comparison Project, (b) the Cirrus Parcel Model Comparison Project (Phase 2), and (c) the developing Hurricane Nora extended outflow model case study project. Past results will be summarized and plans for the upcoming year described. Issues and strategies will be discussed. Prospects for developing improved cloud parameterizations derived from results of GCSS WG2 projects will be assessed. Plans for NASA's CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and Layers - Florida Area Cirrus Experiment) potential opportunities for use of those data for WG2 model simulations (future projects) will be briefly described.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Influence of Ice Particle Surface Roughening on the Global Cloud Radiative Effect

NASA Technical Reports Server (NTRS)

Yi, Bingqi; Yang, Ping; Baum, Bryan A.; LEcuyer, Tristan; Oreopoulos, Lazaros; Mlawer, Eli J.; Heymsfield, Andrew J.; Liou, Kuo-Nan

2013-01-01

Ice clouds influence the climate system by changing the radiation budget and large-scale circulation. Therefore, climate models need to have an accurate representation of ice clouds and their radiative effects. In this paper, new broadband parameterizations for ice cloud bulk scattering properties are developed for severely roughened ice particles. The parameterizations are based on a general habit mixture that includes nine habits (droxtals, hollow/solid columns, plates, solid/hollow bullet rosettes, aggregate of solid columns, and small/large aggregates of plates). The scattering properties for these individual habits incorporate recent advances in light-scattering computations. The influence of ice particle surface roughness on the ice cloud radiative effect is determined through simulations with the Fu-Liou and the GCM version of the Rapid Radiative Transfer Model (RRTMG) codes and the National Center for Atmospheric Research Community Atmosphere Model (CAM, version 5.1). The differences in shortwave (SW) and longwave (LW) radiative effect at both the top of the atmosphere and the surface are determined for smooth and severely roughened ice particles. While the influence of particle roughening on the single-scattering properties is negligible in the LW, the results indicate that ice crystal roughness can change the SW forcing locally by more than 10 W m(exp -2) over a range of effective diameters. The global-averaged SW cloud radiative effect due to ice particle surface roughness is estimated to be roughly 1-2 W m(exp -2). The CAM results indicate that ice particle roughening can result in a large regional SW radiative effect and a small but nonnegligible increase in the global LW cloud radiative effect.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Estimation of ice activation parameters within a particle tracking Lagrangian cloud model using the ensemble Kalman filter to match ISCDAC golden case observations

NASA Astrophysics Data System (ADS)

Reisner, J. M.; Dubey, M. K.

2010-12-01

To both quantify and reduce uncertainty in ice activation parameterizations for stratus clouds occurring in the temperature range between -5 to -10 C ensemble simulations of an ISDAC golden case have been conducted. To formulate the ensemble, three parameters found within an ice activation model have been sampled using a Latin hypercube technique over a parameter range that induces large variability in both number and mass of ice. The ice activation model is contained within a Lagrangian cloud model that simulates particle number as a function of radius for cloud ice, snow, graupel, cloud, and rain particles. A unique aspect of this model is that it produces very low levels of numerical diffusion that enable the model to accurately resolve the sharp cloud edges associated with the ISDAC stratus deck. Another important aspect of the model is that near the cloud edges the number of particles can be significantly increased to reduce sampling errors and accurately resolve physical processes such as collision-coalescence that occur in this region. Thus, given these relatively low numerical errors, as compared to traditional bin models, the sensitivity of a stratus deck to changes in parameters found within the activation model can be examined without fear of numerical contamination. Likewise, once the ensemble has been completed, ISDAC observations can be incorporated into a Kalman filter to optimally estimate the ice activation parameters and reduce overall model uncertainty. Hence, this work will highlight the ability of an ensemble Kalman filter system coupled to a highly accurate numerical model to estimate important parameters found within microphysical parameterizations containing high uncertainty.

Evaluation of Methods to Estimate the Surface Downwelling Longwave Flux during Arctic Winter

NASA Technical Reports Server (NTRS)

Chiacchio, Marc; Francis, Jennifer; Stackhouse, Paul, Jr.

2002-01-01

Surface longwave radiation fluxes dominate the energy budget of nighttime polar regions, yet little is known about the relative accuracy of existing satellite-based techniques to estimate this parameter. We compare eight methods to estimate the downwelling longwave radiation flux and to validate their performance with measurements from two field programs in thc Arctic: the Coordinated Eastern Arctic Experiment (CEAREX ) conducted in the Barents Sea during the autumn and winter of 1988, and the Lead Experiment performed in the Beaufort Sea in the spring of 1992. Five of the eight methods were developed for satellite-derived quantities, and three are simple parameterizations based on surface observations. All of the algorithms require information about cloud fraction, which is provided from the NASA-NOAA Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) polar pathfinder dataset (Path-P): some techniques ingest temperature and moisture profiles (also from Path-P): one-half of the methods assume that clouds are opaque and have a constant geometric thickness of 50 hPa, and three include no thickness information whatsoever. With a somewhat limited validation dataset, the following primary conclusions result: (1) all methods exhibit approximately the same correlations with measurements and rms differences, but the biases range from -34 W sq m (16% of the mean) to nearly 0; (2) the error analysis described here indicates that the assumption of a 50-hPa cloud thickness is too thin by a factor of 2 on average in polar nighttime conditions; (3) cloud-overlap techniques. which effectively increase mean cloud thickness, significantly improve the results; (4) simple Arctic-specific parameterizations performed poorly, probably because they were developed with surface-observed cloud fractions; and (5) the single algorithm that includes an estimate of cloud thickness exhibits the smallest differences from observations.

Continental Shallow Convection Cloud-Base Mass Flux from Doppler Lidar and LASSO Ensemble Large-Eddy Simulations

NASA Astrophysics Data System (ADS)

Vogelmann, A. M.; Zhang, D.; Kollias, P.; Endo, S.; Lamer, K.; Gustafson, W. I., Jr.; Romps, D. M.

2017-12-01

Continental boundary layer clouds are important to simulations of weather and climate because of their impact on surface budgets and vertical transports of energy and moisture; however, model-parameterized boundary layer clouds do not agree well with observations in part because small-scale turbulence and convection are not properly represented. To advance parameterization development and evaluation, observational constraints are needed on critical parameters such as cloud-base mass flux and its relationship to cloud cover and the sub-cloud boundary layer structure including vertical velocity variance and skewness. In this study, these constraints are derived from Doppler lidar observations and ensemble large-eddy simulations (LES) from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Facility Southern Great Plains (SGP) site in Oklahoma. The Doppler lidar analysis will extend the single-site, long-term analysis of Lamer and Kollias [2015] and augment this information with the short-term but unique 1-2 year period since five Doppler lidars began operation at the SGP, providing critical information on regional variability. These observations will be compared to the statistics obtained from ensemble, routine LES conducted by the LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso). An Observation System Simulation Experiment (OSSE) will be presented that uses the LASSO LES fields to determine criteria for which relationships from Doppler lidar observations are adequately sampled to yield convergence. Any systematic differences between the observed and simulated relationships will be examined to understand factors contributing to the differences. Lamer, K., and P. Kollias (2015), Observations of fair-weather cumuli over land: Dynamical factors controlling cloud size and cover, Geophys. Res. Lett., 42, 8693-8701, doi:10.1002/2015GL064534

Assessment of the first indirect radiative effect of ammonium-sulfate-nitrate aerosols in East Asia

NASA Astrophysics Data System (ADS)

Han, Xiao; Zhang, Meigen; Skorokhod, Andrei

2017-11-01

A physically based cloud nucleation parameterization was introduced into an optical properties/radiative transfer module incorporated with the off-line air quality modeling system Regional Atmospheric Modeling System (RAMS)-Models-3 Community Multi Scale Air Quality (CMAQ) to investigate the distribution features of the first indirect radiative effects of sulfate, nitrate, and ammonium-sulfate-nitrate (ASN) over East Asia for the years of 2005, 2010, and 2013. The relationship between aerosol particles and cloud droplet number concentration could be properly described by this parameterization because the simulated cloud fraction and cloud liquid water path were generally reliable compared with Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved data. Simulation results showed that the strong effect of indirect forcing was mainly concentrated in Southeast China, the East China Sea, the Yellow Sea, and the Sea of Japan. The highest indirect radiative forcing of ASN reached -3.47 W m-2 over Southeast China and was obviously larger than the global mean of the indirect forcing of all anthropogenic aerosols. In addition, sulfate provided about half of the contribution to the ASN indirect forcing effect. However, the effect caused by nitrate was weak because the mass burden of nitrate was very low during summer, whereas the cloud fraction was the highest. The analysis indicated that even though the interannual variation of indirect forcing magnitude generally followed the trend of aerosol mass burden from 2005 to 2013, the cloud fraction was an important factor that determined the distribution pattern of indirect forcing. The heaviest aerosol loading in North China did not cause a strong radiative effect because of the low cloud fraction over this region.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

NASA Goddard Earth Sciences Graduate Student Program. [FIRE CIRRUS-II examination of coupling between an upper tropospheric cloud system and synoptic-scale dynamics

NASA Technical Reports Server (NTRS)

Ackerman, Thomas P.

1994-01-01

The evolution of synoptic-scale dynamics associated with a middle and upper tropospheric cloud event that occurred on 26 November 1991 is examined. The case under consideration occurred during the FIRE CIRRUS-II Intensive Field Observing Period held in Coffeyville, KS during Nov. and Dec., 1991. Using data from the wind profiler demonstration network and a temporally and spatially augmented radiosonde array, emphasis is given to explaining the evolution of the kinematically-derived ageostrophic vertical circulations and correlating the circulation with the forcing of an extensively sampled cloud field. This is facilitated by decomposing the horizontal divergence into its component parts through a natural coordinate representation of the flow. Ageostrophic vertical circulations are inferred and compared to the circulation forcing arising from geostrophic confluence and shearing deformation derived from the Sawyer-Eliassen Equation. It is found that a thermodynamically indirect vertical circulation existed in association with a jet streak exit region. The circulation was displaced to the cyclonic side of the jet axis due to the orientation of the jet exit between a deepening diffluent trough and building ridge. The cloud line formed in the ascending branch of the vertical circulation with the most concentrated cloud development occurring in conjunction with the maximum large-scale vertical motion. The relationship between the large scale dynamics and the parameterization of middle and upper tropospheric clouds in large-scale models is discussed and an example of ice water contents derived from a parameterization forced by the diagnosed vertical motions and observed water vapor contents is presented.

Effects of a polar stratosphere cloud parameterization on ozone depletion due to stratospheric aircraft in a two-dimensional model

NASA Technical Reports Server (NTRS)

Considine, David B.; Douglass, Anne R.; Jackman, Charles H.

1994-01-01

A parameterization of Type 1 and 2 polar stratospheric cloud (PSC) formation is presented which is appropriate for use in two-dimensional (2-D) photochemical models of the stratosphere. The calculations of PSC frequency of occurrence and surface area density uses climatological temperature probability distributions obtained from National Meteorological Center data to avoid using zonal mean temperatures, which are not good predictors of PSC behavior. The parameterization does not attempt to model the microphysics of PSCs. The parameterization predicts changes in PSC formation and heterogeneous processing due to perturbations of stratospheric trace constituents. It is therefore useful in assessing the potential effects of a fleet of stratospheric aircraft (high speed civil transports, or HSCTs) on stratospheric composition. the model calculated frequency of PSC occurrence agrees well with a climatology based on stratospheric aerosol measurement (SAM) 2 observations. PSCs are predicted to occur in the tropics. Their vertical range is narrow, however, and their impact on model O3 fields is small. When PSC and sulfate aerosol heterogeneous processes are included in the model calculations, the O3 change for 1980 - 1990 is in substantially better agreement with the total ozone mapping spectrometer (TOMS)-derived O3 trend than otherwise. The overall changes in model O3 response to standard HSCT perturbation scenarios produced by the parameterization are small and tend to decrease the model sensitivity to the HSCT perturbation. However, in the southern hemisphere spring a significant increase in O3 sensitivity to HSCT perturbations is found. At this location and time, increased PSC formation leads to increased levels of active chlorine, which produce the O3 decreases.

Quantified Objectives for Assessing the Contribution of Low Clouds to Climate Sensitivity and Variability

NASA Astrophysics Data System (ADS)

Del Genio, A. D.; Platnick, S. E.; Bennartz, R.; Klein, S. A.; Marchand, R.; Oreopoulos, L.; Pincus, R.; Wood, R.

2016-12-01

Low clouds are central to leading-order questions in climate and subseasonal weather predictability, and are key to the NRC panel report's goals "to understand the signals of the Earth system under a changing climate" and "for improved models and model projections." To achieve both goals requires a mix of continuity observations to document the components of the changing climate and improvements in retrievals of low cloud and boundary layer dynamical/thermodynamic properties to ensure process-oriented observations that constrain the parameterized physics of the models. We discuss four climate/weather objectives that depend sensitively on understanding the behavior of low clouds: 1. Reduce uncertainty in GCM-inferred climate sensitivity by 50% by constraining subtropical low cloud feedbacks. 2. Eliminate the GCM Southern Ocean shortwave flux bias and its effect on cloud feedback and the position of the midlatitude storm track. 3. Eliminate the double Intertropical Convergence Zone bias in GCMs and its potential effects on tropical precipitation over land and the simulation and prediction of El Niño. 4. Increase the subseasonal predictability of tropical warm pool precipitation from 20 to 30 days. We envision advances in three categories of observations that would be highly beneficial for reaching these goals: 1. More accurate observations will facilitate more thorough evaluation of clouds in GCMs. 2. Better observations of the links between cloud properties and the environmental state will be used as the foundation for parameterization improvements. 3. Sufficiently long and higher quality records of cloud properties and environmental state will constrain low cloud feedback purely observationally. To accomplish this, the greatest need is to replace A-Train instruments, which are nearing end-of-life, with enhanced versions. The requirements are sufficient horizontal and vertical resolution to capture boundary layer cloud and thermodynamic spatial structure; more accurate determination of cloud condensate profiles and optical properties; near-coincident observations to permit multi-instrument retrievals and association with dynamic and thermodynamic structure; global coverage; and, for long-term monitoring, measurement and orbit stability and sufficient mission duration.

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).

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.

1996-01-01

An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.

The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations

NASA Astrophysics Data System (ADS)

Zhang, K.; O'Donnell, D.; Kazil, J.; Stier, P.; Kinne, S.; Lohmann, U.; Ferrachat, S.; Croft, B.; Quaas, J.; Wan, H.; Rast, S.; Feichter, J.

2012-03-01

This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Sensitivity experiments are carried out to analyse the effects of these improvements in the process representation on the simulated aerosol properties and global distribution. The new parameterizations that have largest impact on the global mean aerosol optical depth and radiative effects turn out to be the water uptake scheme and cloud microphysics. The former leads to a significant decrease of aerosol water contents in the lower troposphere, and consequently smaller optical depth; the latter results in higher aerosol loading and longer lifetime due to weaker in-cloud scavenging. The combined effects of the new/updated parameterizations are demonstrated by comparing the new model results with those from the earlier version, and against observations. Model simulations are evaluated in terms of aerosol number concentrations against measurements collected from twenty field campaigns as well as from fixed measurement sites, and in terms of optical properties against the AERONET measurements. Results indicate a general improvement with respect to the earlier version. The aerosol size distribution and spatial-temporal variance simulated by HAM2 are in better agreement with the observations. Biases in the earlier model version in aerosol optical depth and in the Ångström parameter have been reduced. The paper also points out the remaining model deficiencies that need to be addressed in the future.

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.

An Economical Analytical Equation for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2018-03-01

By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5

DOE PAGES

Wang, Yong; Zhang, Guang J.

2016-09-29

In this paper, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang-McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large-scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrainedmore » liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large-scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from -52.25 W/m 2 in the standard CAM5 to -48.86 W/m 2, close to -47.16 W/m 2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters are also performed to investigate the sensitivity of simulated climatology to uncertain parameters in the stochastic deep convection scheme.« less

Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5

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

Wang, Yong; Zhang, Guang J.

In this paper, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang-McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large-scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrainedmore » liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large-scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from -52.25 W/m 2 in the standard CAM5 to -48.86 W/m 2, close to -47.16 W/m 2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters are also performed to investigate the sensitivity of simulated climatology to uncertain parameters in the stochastic deep convection scheme.« less

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

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

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison ofmore » the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. Lastly, these large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.« less

Radiatively driven stratosphere-troposphere interactions near the tops of tropical cloud clusters

NASA Technical Reports Server (NTRS)

Churchill, Dean D.; Houze, Robert A., Jr.

1990-01-01

Results are presented of two numerical simulations of the mechanism involved in the dehydration of air, using the model of Churchill (1988) and Churchill and Houze (1990) which combines the water and ice physics parameterizations and IR and solar-radiation parameterization with a convective adjustment scheme in a kinematic nondynamic framework. One simulation, a cirrus cloud simulation, was to test the Danielsen (1982) hypothesis of a dehydration mechanism for the stratosphere; the other was to simulate the mesoscale updraft in order to test an alternative mechanism for 'freeze-drying' the air. The results show that the physical processes simulated in the mesoscale updraft differ from those in the thin-cirrus simulation. While in the thin-cirrus case, eddy fluxes occur in response to IR radiative destabilization, and, hence, no net transfer occurs between troposphere and stratosphere, the mesosphere updraft case has net upward mass transport into the lower stratosphere.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

The terminal area simulation system. Volume 1: Theoretical formulation

NASA Technical Reports Server (NTRS)

Proctor, F. H.

1987-01-01

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

A study of two cases of comma-cloud cyclogenesis using a semigeostrophic model

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

Craig, G.C.; Cho, Hanru

1992-12-01

The linear stability of two atmospheric flows is studied, with basic-state data taken from environments where comma clouds are observed to flow. Each basic state features a baroclinic zone associated with an upper-level jet, with conditional instability on the north side. The semigeostrophic approximation is utilized, along with a simple parameterization for cumulus heating, and the eigenvalue problem is solved employing a Chebyshev spectral technique. 47 refs.

FIRE Arctic Clouds Experiment

NASA Technical Reports Server (NTRS)

Curry, J. A.; Hobbs, P. V.; King, M. D.; Randall, D. A.; Minnis, P.; Issac, G. A.; Pinto, J. O.; Uttal, T.; Bucholtz, A.; Cripe, D. G.;

An energy balance climate model with cloud feedbacks

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.

1984-01-01

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Understanding the Effect of Aerosol Properties on Cloud Droplet Formation during TCAP Field Campaign Report

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

Cziczo, Daniel

2016-05-01

The formation of clouds is an essential element in understanding the Earth’s radiative budget. Liquid water clouds form when the relative humidity exceeds saturation and condensedphase water nucleates on atmospheric particulate matter. The effect of aerosol properties such as size, morphology, and composition on cloud droplet formation has been studied theoretically as well as in the laboratory and field. Almost without exception these studies have been limited to parallel measurements of aerosol properties and cloud formation or collection of material after the cloud has formed, at which point nucleation information has been lost. Studies of this sort are adequate whenmore » a large fraction of the aerosol activates, but correlations and resulting model parameterizations are much more uncertain at lower supersaturations and activated fractions.« less

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Initialization and assimilation of cloud and rainwater in a regional model

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

The initialization and assimilation of cloud and rainwater quantities in a mesoscale regional model was examined. Forecasts of explicit cloud and rainwater are made using conservation equations. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. These physical processes, some of which are parameterized, represent source and sink in terms in the conservation equations. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed.

Parameterizing Grid-Averaged Longwave Fluxes for Inhomogeneous Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Barker, Howard W.; Wielicki, Bruce A.

1997-01-01

This paper examines the relative impacts on grid-averaged longwave flux transmittance (emittance) for Marine Boundary Layer (MBL) cloud fields arising from horizontal variability of optical depth tau and cloud sides, First, using fields of Landsat-inferred tau and a Monte Carlo photon transport algorithm, it is demonstrated that mean all-sky transmittances for 3D variable MBL clouds can be computed accurately by the conventional method of linearly weighting clear and cloudy transmittances by their respective sky fractions. Then, the approximations of decoupling cloud and radiative properties and assuming independent columns are shown to be adequate for computation of mean flux transmittance. Since real clouds have nonzero geometric thicknesses, cloud fractions A'(sub c) presented to isotropic beams usually exceed the more familiar vertically projected cloud fractions A(sub c). It is shown, however, that when A(sub c)less than or equal to 0.9, biases for all-sky transmittance stemming from use of A(sub c) as opposed to A'(sub c) are roughly 2-5 times smaller than, and opposite in sign to, biases due to neglect of horizontal variability of tau. By neglecting variable tau, all-sky transmittances are underestimated often by more than 0.1 for A(sub c) near 0.75 and this translates into relative errors that can exceed 40% (corresponding errors for all-sky emittance are about 20% for most values of A(sub c). Thus, priority should be given to development of General Circulation Model (GCM) parameterizations that account for the effects of horizontal variations in unresolved tau, effects of cloud sides are of secondary importance. On this note, an efficient stochastic model for computing grid-averaged cloudy-sky flux transmittances is furnished that assumes that distributions of tau, for regions comparable in size to GCM grid cells, can be described adequately by gamma distribution functions. While the plane-parallel, homogeneous model underestimates cloud transmittance by about an order of magnitude when 3D variable cloud transmittances are less than or equal to 0.2 and by approx. 20% to 100% otherwise, the stochastic model reduces these biases often by more than 80%.

Modelling ice microphysics of mixed-phase clouds

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Balancing accuracy, efficiency, and flexibility in a radiative transfer parameterization for dynamical models

NASA Astrophysics Data System (ADS)

Pincus, R.; Mlawer, E. J.

2017-12-01

Radiation is key process in numerical models of the atmosphere. The problem is well-understood and the parameterization of radiation has seen relatively few conceptual advances in the past 15 years. It is nonthelss often the single most expensive component of all physical parameterizations despite being computed less frequently than other terms. This combination of cost and maturity suggests value in a single radiation parameterization that could be shared across models; devoting effort to a single parameterization might allow for fine tuning for efficiency. The challenge lies in the coupling of this parameterization to many disparate representations of clouds and aerosols. This talk will describe RRTMGP, a new radiation parameterization that seeks to balance efficiency and flexibility. This balance is struck by isolating computational tasks in "kernels" that expose as much fine-grained parallelism as possible. These have simple interfaces and are interoperable across programming languages so that they might be repalced by alternative implementations in domain-specific langauges. Coupling to the host model makes use of object-oriented features of Fortran 2003, minimizing branching within the kernels and the amount of data that must be transferred. We will show accuracy and efficiency results for a globally-representative set of atmospheric profiles using a relatively high-resolution spectral discretization.

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

Wong, May Wai San; Ovchinnikov, Mikhail; Wang, Minghuai

Potential ways of parameterizing vertical turbulent fluxes of hydrometeors are examined using a high-resolution cloud-resolving model. The cloud-resolving model uses the Morrison microphysics scheme, which contains prognostic variables for rain, graupel, ice, and snow. A benchmark simulation with a horizontal grid spacing of 250 m of a deep convection case carried out to evaluate three different ways of parameterizing the turbulent vertical fluxes of hydrometeors: an eddy-diffusion approximation, a quadrant-based decomposition, and a scaling method that accounts for within-quadrant (subplume) correlations. Results show that the down-gradient nature of the eddy-diffusion approximation tends to transport mass away from concentrated regions, whereasmore » the benchmark simulation indicates that the vertical transport tends to transport mass from below the level of maximum to aloft. Unlike the eddy-diffusion approach, the quadri-modal decomposition is able to capture the signs of the flux gradient but underestimates the magnitudes. The scaling approach is shown to perform the best by accounting for within-quadrant correlations, and improves the results for all hydrometeors except for snow. A sensitivity study is performed to examine how vertical transport may affect the microphysics of the hydrometeors. The vertical transport of each hydrometeor type is artificially suppressed in each test. Results from the sensitivity tests show that cloud-droplet-related processes are most sensitive to suppressed rain or graupel transport. In particular, suppressing rain or graupel transport has a strong impact on the production of snow and ice aloft. Lastly, a viable subgrid-scale hydrometeor transport scheme in an assumed probability density function parameterization is discussed.« less

Parameterization of In-Cloud Aerosol Scavenging Due To Atmospheric Ionization: 2. Effects of Varying Particle Density

NASA Astrophysics Data System (ADS)

Zhang, Liang; Tinsley, Brian A.

2018-03-01

Simulations and parameterization of collision rate coefficients for aerosol particles with 3 μm radius droplets have been extended to a range of particle densities up to 2,000 kg m-3 for midtropospheric ( 5 km) conditions (540 hPa, -17°C). The increasing weight has no effect on collisions for particle radii less than 0.2 μm, but for greater radii the weight effect becomes significant and usually decreases the collision rate coefficient. When increasing size and density of particles make the fall speed of the particle relative to undisturbed air approach to that of the droplet, the effect of the particle falling away in the stagnation region ahead of the droplet becomes important, and the probability of frontside collisions can decrease to zero. Collisions on the rear side of the droplet can be enhanced as particle weight increases, and for this the weight effect tends to increase the rate coefficients. For charges on the droplet and for large particles with density ρ < 1,000 kg m-3 the predominant effect increases in rate coefficient due to the short-range attractive image electric force. With density ρ above about 1,000 kg m-3, the stagnation region prevents particles moving close to the droplet and reduces the effect of these short-range forces. Together with previous work, it is now possible to obtain collision rate coefficients for realistic combinations of droplet charge, particle charge, droplet radius, particle radius, particle density, and relative humidity in clouds. The parameterization allows rapid access to these values for use in cloud models.

Development and Testing of Coupled Land-surface, PBL and Shallow/Deep Convective Parameterizations within the MM5

NASA Technical Reports Server (NTRS)

Stauffer, David R.; Seaman, Nelson L.; Munoz, Ricardo C.

2000-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins using a 3-D mesoscale model, the PSUINCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. It was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having a detailed land-surface parameterization, an advanced boundary-layer parameterization, and a more complete shallow convection parameterization than are available in most current models. The methodology was based on the application in the MM5 of new or recently improved parameterizations covering these three physical processes. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the Southern Great Plains (SGP): (1) the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) described by Wetzel and Boone; (2) the 1.5-order turbulent kinetic energy (TKE)-predicting scheme of Shafran et al.; and (3) the hybrid-closure sub-grid shallow convection parameterization of Deng. Each of these schemes has been tested extensively through this study and the latter two have been improved significantly to extend their capabilities.

Assessment of different models for computing the probability of a clear line of sight

NASA Astrophysics Data System (ADS)

Bojin, Sorin; Paulescu, Marius; Badescu, Viorel

2017-12-01

This paper is focused on modeling the morphological properties of the cloud fields in terms of the probability of a clear line of sight (PCLOS). PCLOS is defined as the probability that a line of sight between observer and a given point of the celestial vault goes freely without intersecting a cloud. A variety of PCLOS models assuming the cloud shape hemisphere, semi-ellipsoid and ellipsoid are tested. The effective parameters (cloud aspect ratio and absolute cloud fraction) are extracted from high-resolution series of sunshine number measurements. The performance of the PCLOS models is evaluated from the perspective of their ability in retrieving the point cloudiness. The advantages and disadvantages of the tested models are discussed, aiming to a simplified parameterization of PCLOS models.

A network approach to the geometric structure of shallow cloud fields

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations. As an outlook, we discuss how a similar network approach can be applied to describe and quantify the geometric structure of shallow cumulus cloud fields.

Improving Forecasts of Cumulus: An Intersection of the Renewable Energy and Climate Science Communities

NASA Astrophysics Data System (ADS)

Berg, L. K.; Gustafson, W. I., Jr.; Kassianov, E.; Long, C. N.

2015-12-01

Accurate forecasts of broken cloud fields and their associated impact on the downwelling solar irradiance has remained a challenge to the renewable energy industry. Likewise, shallow cumulus play an important role in the Earth's radiation budget and hydrologic cycle and are of interest to the weather forecasting and climate science communities. The main challenge associated with predicting these clouds are their relatively small size (on the order of a kilometer or less) relative to the model grid spacing. Recently, however, there have been significant efforts put into improving forecasts of shallow clouds and the associated temporal and spatial variability of the solar irradiance that they induce. As an example of these efforts, we will describe recent modifications to the standard Kain-Fritsch parameterization as applied within the Weather Research and Forecasting (WRF) model that are designed to improve predictions of the macroscale and microscale structure of shallow cumulus. These modifications are shown to lead to a realistic increase in the simulated cloud fraction and associated decrease in the solar irradiance. We will evaluate our results using data collected at the Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains site, which is located in north-central Oklahoma. Our team has analyzed over 5 years of data collected at this site to document the macroscale structure of the clouds (including cloud fraction, cloud-base and cloud-top height) as well as their impact on the downwelling shortwave and longwave irradiance. One particularly interesting impact of shallow cumuli is the enhancement of the diffuse radiation, such that during periods in which the sun is not blocked, the observed irradiance can be significantly larger than the corresponding clear sky case. To date, this feature is not accurately represented by models that apply the plane-parallel assumption applied in the standard radiation parameterizations.

Modeling the MJO rain rates using parameterized large scale dynamics: vertical structure, radiation, and horizontal advection of dry air

NASA Astrophysics Data System (ADS)

Wang, S.; Sobel, A. H.; Nie, J.

2015-12-01

Two Madden Julian Oscillation (MJO) events were observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign. Precipitation rates and large-scale vertical motion profiles derived from the DYNAMO northern sounding array are simulated in a small-domain cloud-resolving model using parameterized large-scale dynamics. Three parameterizations of large-scale dynamics --- the conventional weak temperature gradient (WTG) approximation, vertical mode based spectral WTG (SWTG), and damped gravity wave coupling (DGW) --- are employed. The target temperature profiles and radiative heating rates are taken from a control simulation in which the large-scale vertical motion is imposed (rather than directly from observations), and the model itself is significantly modified from that used in previous work. These methodological changes lead to significant improvement in the results.Simulations using all three methods, with imposed time -dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large-scale vertical motion profile, however. WTG produces the most top-heavy and noisy profiles, while DGW's is smoother with a peak in midlevels. SWTG produces a smooth profile, somewhere between WTG and DGW, and in better agreement with observations than either of the others. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top-heaviness of large-scale vertical motion during the MJO active phases, while experiments in which the effect of cloud on radiation are disabled indicate that cloud-radiative interaction significantly amplifies the MJO. Experiments in which interactive radiation is used produce poorer agreement with observation than those with imposed time-varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and cloud-radiative feedback to the dynamics of the MJO, as well as to accurate simulation and prediction of it in models.

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

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

Song, Hua; Zhang, Zhibo; Ma, Po-Lun

This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less

Impact of cloud timing on surface temperature and related hydroclimatic dynamics

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Yin, J.

2015-12-01

Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.

EAULIQ: The Next Generation

NASA Technical Reports Server (NTRS)

Randall, David A.; Fowler, Laura D.

1999-01-01

This report summarizes the design of a new version of the stratiform cloud parameterization called Eauliq; the new version is called Eauliq NG. The key features of Eauliq NG are: (1) a prognostic fractional area covered by stratiform cloudiness, following the approach developed by M. Tiedtke for use in the ECMWF model; (2) separate prognostic thermodynamic variables for the clear and cloudy portions of each grid cell; (3) separate vertical velocities for the clear and cloudy portions of each grid cell, allowing the model to represent some aspects of observed mesoscale circulations; (4) cumulus entrainment from both the clear and cloudy portions of a grid cell, and cumulus detrainment into the cloudy portion only; and (5) the effects of the cumulus-induced subsidence in the cloudy portion of a grid cell on the cloud water and ice there. In this paper we present the mathematical framework of Eauliq NG; a discussion of cumulus effects; a new parameterization of lateral mass exchanges between clear and cloudy regions; and a theory to determine the mesoscale mass circulation, based on the hypothesis that the stratiform clouds remain neutrally buoyant through time and that the mesoscale circulations are the mechanism which makes this possible. An appendix also discusses some time-differencing methods.

Optimizing the Betts-Miller-Janjic cumulus parameterization with Intel Many Integrated Core (MIC) architecture

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.-L.

2015-10-01

The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

Nonspherical and Spherical Characterization of Ice in Hurricane Erin for Wideband Passive Microwave Comparisons

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Holthaus, Eric; Albers, Cerese; Kim, Min-Jeong

2007-01-01

In order to better understand the characteristics of frozen cloud particles in hurricane systems, computed brightness temperatures were compared with radiometric observations of Hurricane Erin (2001) from the NASA ER-2 aircraft. The focus was oil the frozen particle microphysics and the high frequencies (2 85 GHz) that are particularly sensitive to frozen particles. Frozen particles in hurricanes are an indicator of increasing hurricane intensity. In fact "hot towers" associated with increasing hurricane intensity are composed of frozen ice cloud particles. (They are called hot towers because their column of air is warmer than the surrounding air temperature, but above about 5-7 km to the tops of the towers at 15-19 km, the cloud particles are frozen.) This work showed that indeed, one can model information about cloud ice particle characteristics and indicated that nonspherical ice shapes, instead of spherical particles, provided the best match to the observations. Overall, this work shows that while non-spherical particles show promise, selecting and modeling a proper ice particle parameterization can be difficult and additional in situ measurements are needed to define and validate appropriate parameterizations. This work is important for developing Global Precipitation Measurement (GPM) mission satellite algorithms for the retrieval of ice characteristics both above the melting layer, as in Hurricane Erin, and for ice particles that reach the surface as falling snow.

Potential sea salt aerosol sources from frost flowers in the pan-Arctic region

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

Xu, Li; Russell, Lynn M.; Burrows, Susannah M.

In order to better represent observed wintertime aerosol concentrations at Barrow, Alaska, we implemented an observationally-based parameterization for estimating sea salt production from frost flowers in the Community Earth System Model (CESM). In this work, we evaluate the potential influence of this sea salt source on the pan-Arctic (60ºN-90ºN) climate. Results show that frost flower salt emissions substantially increase the modeled surface sea salt aerosol concentration in the winter months when new sea ice and frost flowers are present. The parameterization reproduces both the magnitude and seasonal variation of the observed submicron sea salt aerosol concentration at surface in Barrowmore » during winter much better than the standard CESM simulation without a frost-flower salt particle source. Adding these frost flower salt particle emissions increases aerosol optical depth by 10% and results in a small cooling at surface. The increase in salt particle mass concentrations of a factor of 8 provides nearly two times the cloud condensation nuclei concentration, as well as 10% increases in cloud droplet number and 40% increases in liquid water content near coastal regions adjacent to continents. These cloud changes reduce longwave cloud forcing by 3% and cause a small surface warming, increasing the downward longwave flux at the surface by 2 W m-2 in the pan-Arctic under the present-day climate.« less

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;

Sensitivity Studies of Dust Ice Nuclei Effect on Cirrus Clouds with the Community Atmosphere Model CAM5

NASA Technical Reports Server (NTRS)

Liu, Xiaohong; Zhang, Kai; Jensen, Eric J.; Gettelman, Andrew; Barahona, Donifan; Nenes, Athanasios; Lawson, Paul

2012-01-01

In this study the effect of dust aerosol on upper tropospheric cirrus clouds through heterogeneous ice nucleation is investigated in the Community Atmospheric Model version 5 (CAM5) with two ice nucleation parameterizations. Both parameterizations consider homogeneous and heterogeneous nucleation and the competition between the two mechanisms in cirrus clouds, but differ significantly in the number concentration of heterogeneous ice nuclei (IN) from dust. Heterogeneous nucleation on dust aerosol reduces the occurrence frequency of homogeneous nucleation and thus the ice crystal number concentration in the Northern Hemisphere (NH) cirrus clouds compared to simulations with pure homogeneous nucleation. Global and annual mean shortwave and longwave cloud forcing are reduced by up to 2.0+/-0.1Wm (sup-2) (1 uncertainty) and 2.4+/-0.1Wm (sup-2), respectively due to the presence of dust IN, with the net cloud forcing change of -0.40+/-0.20W m(sup-2). Comparison of model simulations with in situ aircraft data obtained in NH mid-latitudes suggests that homogeneous ice nucleation may play an important role in the ice nucleation at these regions with temperatures of 205-230 K. However, simulations overestimate observed ice crystal number concentrations in the tropical tropopause regions with temperatures of 190- 205 K, and overestimate the frequency of occurrence of high ice crystal number concentration (greater than 200 L(sup-1) and underestimate the frequency of low ice crystal number concentration (less than 30 L(sup-1) at NH mid-latitudes. These results highlight the importance of quantifying the number concentrations and properties of heterogeneous IN (including dust aerosol) in the upper troposphere from the global perspective.

Simulation of Optical Properties and Direct and Indirect Radiative Effects of Smoke Aerosols Over Marine Stratocumulus Clouds During Summer 2008 in California With the Regional Climate Model RegCM

NASA Astrophysics Data System (ADS)

Mallet, M.; Solmon, F.; Roblou, L.; Peers, F.; Turquety, S.; Waquet, F.; Jethva, H.; Torres, O.

2017-10-01

The regional climate model RegCM has been modified to better account for the climatic effects of biomass-burning particles. Smoke aerosols are represented by new tracers with consistent radiative and hygroscopic properties to simulate the direct radiative forcing (DRF), and a new parameterization has been integrated for relating the droplet number concentration to the aerosol concentration for marine stratocumulus clouds (Sc). RegCM has been tested during the summer of 2008 over California, when extreme concentration of smoke, together with the presence of Sc, is observed. This work indicates that significant aerosol optical depth (AOD) ( 1-2 at 550 nm) is related to the intense 2008 fires. Compared to Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer, the regional pattern of RegCM AOD is well represented although the magnitude is lower than satellite observations. Comparisons with Polarization and Directionality of Earth Reflectances (POLDER) above-clouds aerosol optical depth (ACAOD) show the ability of RegCM to simulate realistic ACAOD during the transport of smoke above the Pacific Ocean. The simulated single scattering albedo is 0.90 (at 550 nm) near biomass-burning sources, consistent with OMI and POLDER, and smoke leads to shortwave heating rates 1.5-2°K d-1. RegCM is not able to correctly resolve the daily patterns in cloud properties notably due to its coarse horizontal resolutions. However, the changes in the sign of the DRF at top of atmosphere (TOA) (negative to positive) from clear-sky to all-sky conditions is well simulated. Finally, the "aerosol-cloud" parameterization allows simulating an increase of the cloud optical depth for significant concentrations, leading to large perturbations of radiative fluxes at TOA.

Using large eddy simulations to reveal the size, strength, and phase of updraft and downdraft cores of an Arctic mixed-phase stratocumulus cloud

DOE PAGES

Roesler, Erika L.; Posselt, Derek J.; Rood, Richard B.

2017-04-06

Three-dimensional large eddy simulations (LES) are used to analyze a springtime Arctic mixed-phase stratocumulus observed on 26 April 2008 during the Indirect and Semi-Direct Aerosol Campaign. Two subgrid-scale turbulence parameterizations are compared. The first scheme is a 1.5-order turbulent kinetic energy (1.5-TKE) parameterization that has been previously applied to boundary layer cloud simulations. The second scheme, Cloud Layers Unified By Binormals (CLUBB), provides higher-order turbulent closure with scale awareness. The simulations, in comparisons with observations, show that both schemes produce the liquid profiles within measurement variability but underpredict ice water mass and overpredict ice number concentration. The simulation using CLUBBmore » underpredicted liquid water path more than the simulation using the 1.5-TKE scheme, so the turbulent length scale and horizontal grid box size were increased to increase liquid water path and reduce dissipative energy. The LES simulations show this stratocumulus cloud to maintain a closed cellular structure, similar to observations. The updraft and downdraft cores self-organize into a larger meso-γ-scale convective pattern with the 1.5-TKE scheme, but the cores remain more isotropic with the CLUBB scheme. Additionally, the cores are often composed of liquid and ice instead of exclusively containing one or the other. Furthermore, these results provide insight into traditionally unresolved and unmeasurable aspects of an Arctic mixed-phase cloud. From analysis, this cloud's updraft and downdraft cores appear smaller than other closed-cell stratocumulus such as midlatitude stratocumulus and Arctic autumnal mixed-phase stratocumulus due to the weaker downdrafts and lower precipitation rates.« less

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Bacmeister, Julio; Bosilovich, Michael; Pittman, Jasna

2007-01-01

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

The Dominant Snow-forming Process in Warm and Cold Mixed-phase Orographic Clouds: Effects of Cloud Condensation Nuclei and Ice Nuclei

NASA Astrophysics Data System (ADS)

Fan, J.; Rosenfeld, D.; Leung, L. R.; DeMott, P. J.

2014-12-01

Mineral dust aerosols often observed over California in winter and spring from long-range transport can be efficient ice nuclei (IN) and enhance snow precipitation in mixed-phase orographic clouds. On the other hand, local pollution particles can serve as good CCN and suppress warm rain, but their impacts on cold rain processes are uncertain. The main snow-forming mechanism in warm and cold mixed-phase orographic clouds (refer to as WMOC and CMOC, respectively) could be very different, leading to different precipitation response to CCN and IN. We have conducted 1-km resolution model simulations using the Weather Research and Forecasting (WRF) model coupled with a spectral-bin cloud microphysical model for WMOC and CMOC cases from CalWater2011. We investigated the response of cloud microphysical processes and precipitation to CCN and IN with extremely low to extremely high concentrations using ice nucleation parameterizations that connect with dust and implemented based on observational evidences. We find that riming is the dominant process for producing snow in WMOC while deposition plays a more important role than riming in CMOC. Increasing IN leads to much more snow precipitation mainly due to an increase of deposition in CMOC and increased rimming in WMOC. Increasing CCN decreases precipitation in WMOC by efficiently suppressing warm rain, although snow is increased. In CMOC where cold rain dominates, increasing CCN significantly increases snow, leading to a net increase in precipitation. The sensitivity of supercooled liquid to CCN and IN has also been analyzed. The mechanism for the increased snow by CCN and caveats due to uncertainties in ice nucleation parameterizations will be discussed.

High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2): Large Eddy Simulation Study Over Germany

NASA Astrophysics Data System (ADS)

Dipankar, A.; Stevens, B. B.; Zängl, G.; Pondkule, M.; Brdar, S.

2014-12-01

The effect of clouds on large scale dynamics is represented in climate models through parameterization of various processes, of which the parameterization of shallow and deep convection are particularly uncertain. The atmospheric boundary layer, which controls the coupling to the surface, and which defines the scale of shallow convection, is typically 1 km in depth. Thus, simulations on a O(100 m) grid largely obviate the need for such parameterizations. By crossing this threshold of O(100m) grid resolution one can begin thinking of large-eddy simulation (LES), wherein the sub-grid scale parameterization have a sounder theoretical foundation. Substantial initiatives have been taken internationally to approach this threshold. For example, Miura et al., 2007 and Mirakawa et al., 2014 approach this threshold by doing global simulations, with (gradually) decreasing grid resolution, to understand the effect of cloud-resolving scales on the general circulation. Our strategy, on the other hand, is to take a big leap forward by fixing the resolution at O(100 m), and gradually increasing the domain size. We believe that breaking this threshold would greatly help in improving the parameterization schemes and reducing the uncertainty in climate predictions. To take this forward, the German Federal Ministry of Education and Research has initiated a project on HD(CP)2 that aims for a limited area LES at resolution O(100 m) using the new unified modeling system ICON (Zängl et al., 2014). In the talk, results from the HD(CP)2 evaluation simulation will be shown that targets high resolution simulation over a small domain around Jülich, Germany. This site is chosen because high resolution HD(CP)2 Observational Prototype Experiment took place in this region from 1.04.2013 to 31.05.2013, in order to critically evaluate the model. Nesting capabilities of ICON is used to gradually increase the resolution from the outermost domain, which is forced from the COSMO-DE data, to the innermost and finest resolution domain centered around Jülich (see Fig. 1 top panel). Furthermore, detailed analyses of the simulation results against the observation data will be presented. A reprsentative figure showing time series of column integrated water vapor (IWV) for both model and observation on 24.04.2013 is shown in bottom panel of Fig. 1.

A microphysical parameterization of aqSOA and sulfate formation in clouds

NASA Astrophysics Data System (ADS)

McVay, Renee; Ervens, Barbara

2017-07-01

Sulfate and secondary organic aerosol (cloud aqSOA) can be chemically formed in cloud water. Model implementation of these processes represents a computational burden due to the large number of microphysical and chemical parameters. Chemical mechanisms have been condensed by reducing the number of chemical parameters. Here an alternative is presented to reduce the number of microphysical parameters (number of cloud droplet size classes). In-cloud mass formation is surface and volume dependent due to surface-limited oxidant uptake and/or size-dependent pH. Box and parcel model simulations show that using the effective cloud droplet diameter (proportional to total volume-to-surface ratio) reproduces sulfate and aqSOA formation rates within ≤30% as compared to full droplet distributions; other single diameters lead to much greater deviations. This single-class approach reduces computing time significantly and can be included in models when total liquid water content and effective diameter are available.

Impact of aerosols, dust, water vapor and clouds on fair weather PG and implications for the Carnegie curve

NASA Astrophysics Data System (ADS)

Kourtidis, Konstantinos; Georgoulias, Aristeidis

2017-04-01

We studied the impact of anthropogenic aerosols, fine mode natural aerosols, Saharan dust, atmospheric water vapor, cloud fraction, cloud optical depth and cloud top height on the magnitude of fair weather PG at the rural station of Xanthi. Fair weather PG was measured in situ while the other parameters were obtained from the MODIS instrument onboard the Terra and Aqua satellites. All of the above parameteres were found to impact fair weather PG magnitude. Regarding aerosols, the impact was larger for Saharan dust and fine mode natural aerosols whereas regarding clouds the impact was larger for cloud fraction while less than that of aerosols. Water vapour and ice precipitable water were also found to influence fair weather PG. Since aerosols and water are ubiquitous in the atmosphere and exhibit large spatial and temporal variability, we postulate that our understanding of the Carnegie curve might need revision.

Cirrus microphysics and radiative transfer: Cloud field study on October 28, 1986

NASA Technical Reports Server (NTRS)

Kinne, Stefan; Ackerman, Thomas P.; Heymsfield, Andrew J.; Valero, Francisco P. J.; Sassen, Kenneth; Spinhirne, James D.

1990-01-01

The radiative properties of cirrus clouds present one of the unresolved problems in weather and climate research. Uncertainties in ice particle amount and size and, also, the general inability to model the single scattering properties of their usually complex particle shapes, prevent accurate model predictions. For an improved understanding of cirrus radiative effects, field experiments, as those of the Cirrus IFO of FIRE, are necessary. Simultaneous measurements of radiative fluxes and cirrus microphysics at multiple cirrus cloud altitudes allows the pitting of calculated versus measured vertical flux profiles; with the potential to judge current cirrus cloud modeling. Most of the problems in this study are linked to the inhomogeneity of the cloud field. Thus, only studies on more homogeneous cirrus cloud cases promises a possibility to improve current cirrus parameterizations. Still, the current inability to detect small ice particles will remain as a considerable handicap.

On the Variability of Wilson Currents by Storm Type and Phase

NASA Technical Reports Server (NTRS)

Deierling, Wiebke; Kalb, Christina; Mach, Douglas; Liu, Chuntao; Peterson, Michael; Blakeslee, Richard

2014-01-01

Storm total conduction currents from electrified clouds are thought to play a major role in maintaining the potential difference between the earth's surface and the upper atmosphere within the Global Electric Circuit (GEC). However, it is not entirely known how the contributions of these currents vary by cloud type and phase of the clouds life cycle. Estimates of storm total conduction currents were obtained from data collected over two decades during multiple field campaigns involving the NASA ER-2 aircraft. In this study the variability of these currents by cloud type and lifecycle is investigated. We also compared radar derived microphysical storm properties with total storm currents to investigate whether these storm properties can be used to describe the current variability of different electrified clouds. The ultimate goal is to help improve modeling of the GEC via quantification and improved parameterization of the conduction current contribution of different cloud types.

Using Satellite Observations to Infer the Relationship Between Cold Pools and Subsequent Convection Development

NASA Technical Reports Server (NTRS)

Elsaesser, Gregory

2015-01-01

Cold pools are increasingly being recognized as important players in the evolution of both shallow and deep convection; hence, the incorporation of cold pool processes into a number of recently developed convective parameterizations. Unfortunately, observations serving to inform cold pool parameterization development are limited to select field programs and limited radar domains. However, a number of recent studies have noted that cold pools are often associated with arcs-lines of shallow clouds traversing 10 100 km in visible satellite imagery. Boundary layer thermodynamic perturbations are plausible at such scales, coincident with such mesoscale features. Atmospheric signatures of features at these spatial scales are potentially observable from satellites. In this presentation, we discuss recent work that uses multi-sensor, high-resolution satellite products for observing mesoscale wind vector fluctuations and boundary layer temperature depressions attributed to cold pools produced by antecedent convection. The relationship to subsequent convection as well as convective system longevity is discussed. As improvements in satellite technology occur and efforts to reduce noise in high-resolution orbital products progress, satellite pixel level (10 km) thermodynamic and dynamic (e.g. mesoscale convergence) parameters can increasingly serve as useful benchmarks for constraining convective parameterization development, including for regimes where organized convection contributes substantially to the cloud and rainfall climatology.

Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain-Fritsch Cumulus Parameterization.

PubMed

Sims, Aaron P; Alapaty, Kiran; Raman, Sethu

2017-01-01

Two mesoscale circulations, the Sandhills circulation and the sea breeze, influence the initiation of deep convection over the Sandhills and the coast in the Carolinas during the summer months. The interaction of these two circulations causes additional convection in this coastal region. Accurate representation of mesoscale convection is difficult as numerical models have problems with the prediction of the timing, amount, and location of precipitation. To address this issue, the authors have incorporated modifications to the Kain-Fritsch (KF) convective parameterization scheme and evaluated these mesoscale interactions using a high-resolution numerical model. The modifications include changes to the subgrid-scale cloud formulation, the convective turnover time scale, and the formulation of the updraft entrainment rates. The use of a grid-scaling adjustment parameter modulates the impact of the KF scheme as a function of the horizontal grid spacing used in a simulation. Results indicate that the impact of this modified cumulus parameterization scheme is more effective on domains with coarser grid sizes. Other results include a decrease in surface and near-surface temperatures in areas of deep convection (due to the inclusion of the effects of subgrid-scale clouds on the radiation), improvement in the timing of convection, and an increase in the strength of deep convection.

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

Mitchell, David L.

It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V m, in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interactmore » with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V m, and then proceed to calculate V m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V m calculations than simply using the 2D-S measurements to directly calculate V m. By calculating V m directly from the measured PSD, ice particle projected area and estimated mass, more accurate estimates of V m are obtained. These V m values were then parameterized for climate models by relating them to (1) sampling temperature and ice water content (IWC) and (2) the effective diameter (D e) of the ice PSD. Parameterization (1) is appropriate for climate models having single-moment microphysical schemes whereas (2) is appropriate for double-moment microphysical schemes and yields more accurate V m estimates. These parameterizations were developed for tropical cirrus clouds, Arctic cirrus, mid-latitude synoptic cirrus and mid-latitude anvil cirrus clouds based on field campaigns in these regions. An important but unexpected result of this research was the discovery of microphysical evidence indicating the mechanisms by which ice crystals are produced in cirrus clouds. This evidence, derived from PSD measurements, indicates that homogeneous freezing ice nucleation dominates in mid-latitude synoptic cirrus clouds, whereas heterogeneous ice nucleation processes dominate in mid-latitude anvil cirrus. Based on these findings, D e was parameterized in terms of temperature (T) for conditions dominated by (1) homo- and (2) heterogeneous ice nucleation. From this, an experiment was designed for global climate models (GCMs). The net radiative forcing from cirrus clouds may be affected by the means ice is produced (homo- or heterogeneously), and this net forcing contributes to climate sensitivity (i.e. the change in mean global surface temperature resulting from a doubling of CO 2). The objective of this GCM experiment was to determine how a change in ice nucleation mode affects the predicted global radiation balance. In the first simulation (Run 1), the D e-T relationship for homogeneous nucleation is used at all latitudes, while in the second simulation (Run 2), the D e-T relationship for heterogeneous nucleation is used at all latitudes. For both runs, V m is calculated from D e. Two GCMs were used; the Community Atmosphere Model version 5 (CAM5) and a European GCM known as ECHAM5 (thanks to our European colleagues who collaborated with us). Similar results were obtained from both GCMs in the Northern Hemisphere mid-latitudes, with a net cooling of ~ 1.0 W m -2 due to heterogeneous nucleation, relative to Run 1. The mean global net cooling was 2.4 W m -2 for the ECHAM5 GCM while CAM5 produced a mean global net cooling of about 0.8 W m -2. This dependence of the radiation balance on nucleation mode is substantial when one considers the direct radiative forcing from a CO 2 doubling is 4 W m -2. The differences between GCMs in mean global net cooling estimates may demonstrate a need for improving the representation of cirrus clouds in GCMs, including the coupling between microphysical and radiative properties. Unfortunately, after completing this GCM experiment, we learned from the company that provided the 2D-S microphysical data that the data was corrupted due to a computer program coding problem. Therefore the microphysical data had to be reprocessed and reanalyzed, and the GCM experiments were redone under our current ASR project but using an improved experimental design.« less

Development of a Global Multilayered Cloud Retrieval System

NASA Technical Reports Server (NTRS)

Huang, J.; Minnis, P.; Lin, B.; Yi, Y.; Ayers, J. K.; Khaiyer, M. M.; Arduini, R.; Fan, T.-F

2004-01-01

A more rigorous multilayered cloud retrieval system has been developed to improve the determination of high cloud properties in multilayered clouds. The MCRS attempts a more realistic interpretation of the radiance field than earlier methods because it explicitly resolves the radiative transfer that would produce the observed radiances. A two-layer cloud model was used to simulate multilayered cloud radiative characteristics. Despite the use of a simplified two-layer cloud reflectance parameterization, the MCRS clearly produced a more accurate retrieval of ice water path than simple differencing techniques used in the past. More satellite data and ground observation have to be used to test the MCRS. The MCRS methods are quite appropriate for interpreting the radiances when the high cloud has a relatively large optical depth (tau(sub I) greater than 2). For thinner ice clouds, a more accurate retrieval might be possible using infrared methods. Selection of an ice cloud retrieval and a variety of other issues must be explored before a complete global application of this technique can be implemented. Nevertheless, the initial results look promising.

Intercomparison of methods of coupling between convection and large-scale circulation: 2. Comparison over nonuniform surface conditions

DOE PAGES

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

2016-03-18

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison ofmore » the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. Lastly, these large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.« less

Parameterization of aerosol scavenging due to atmospheric ionization under varying relative humidity

NASA Astrophysics Data System (ADS)

Zhang, Liang; Tinsley, Brian A.

2017-05-01

Simulations and parameterizations of the modulation of aerosol scavenging by electric charges on particles and droplets for different relative humidities have been made for 3 μm radii droplets and a wide range of particle radii. For droplets and particles with opposite-sign charges, the attractive Coulomb force increases the collision rate coefficients above values due to other forces. With same-sign charges, the repulsive Coulomb force decreases the rate coefficients, and the short-range attractive image forces become important. The phoretic forces are attractive for relative humidity less than 100% and repulsive for relative humidity greater than 100% and have increasing overall effect for particle radii up to about 1 μm. There is an analytic solution for rate coefficients if only inverse square forces are present, but due to the presence of image forces, and for larger particles the intercept, weight, and the flow around the particle affecting the droplet trajectory, the simulated results usually depart far from the analytic solution. We give simple empirical parameterization formulas for some cases and more complex parameterizations for more exact fits to the simulated results. The results can be used in cloud models with growing droplets, as in updrafts, as well as with evaporating droplets in downdrafts. There is considered to be little scavenging of uncharged ice-forming nuclei in updrafts, but with charged ice-forming nuclei it is possible for scavenging in updrafts in cold clouds to produce contact ice nucleation. Scavenging in updrafts below the freezing level produces immersion nuclei that promote enhanced freezing as droplets rise above it.

Modeling of Cloud/Radiation Processes for Large-Scale Clouds and Tropical Anvils

DTIC Science & Technology

1994-05-31

Bergeron- Findeisen process. The saturation vapor pressure over ice is less than 2.4. Radiative transfer parameterization that over water. As a result, ice...nucleation to generate ice dN ) ’- if T>- -20 0C crystals, depositional growth to simulate the T•’= 0j At (3.7) Bergeron- Findeisen process, sublimation...and (0 if T< - 200C. melting of ice crystals, and gravitational settling to deplete the ice crystals. The Bergeron- Findeisen Here, N, +,,, and N, are

FIRE Science Results 1988

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor); Wagner, H. Scott (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation program that seeks to address the issues of a basic understanding and parameterizations of cirrus and marine stratocumulus cloud systems and ISCCP data products. The papers describe research analysis of data collected at the 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, and the Extended Time Observations. The papers are grouped into sessions on satellite studies, lidar/radiative properties/microphysical studies, radiative properties, thermodynamic and dynamic properties, case studies, and large scale environment and modeling studies.

Final Report for DOE Grant DE-FG02-06ER64160 Retrieval of Cloud Properties and Direct Testing of Cloud and Radiation Parameterizations using ARM Observations.

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

Donovan, David Patrick

This report briefly summaries the work performed at KNMI under DOE Grant DE-FG02-06ER64160 which, in turn was conducted in support of DOE Grant DE-FG02-90ER61071 lead by E. Clothieux of Penn. State U. The specific work at KNMI revolved around the development and application of the EarthCARE simulator to ground-based multi-sensor simulations.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

PubMed Central

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F.; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C.

2017-01-01

Background Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Objective Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Methods Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson’s disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Results Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Conclusion Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation. PMID:28441410

Using ARM Measurements to Understand and Reduce the Double ITCZ Biases in the Community Atmospheric Model

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

Zhang, Minghua

1. Understanding of the observed variability of ITCZ in the equatorial eastern Pacific. The annual mean precipitation in the eastern Pacific has a maximum zonal band north of the equator in the ITCZ where the maximum SST is located. During the boreal spring (referring to February, March, and April throughout the present paper), because of the accumulated solar radiation heating and oceanic heat transport, a secondary maximum of SST exists in the southeastern equatorial Pacific. Associated with this warm SST is also a seasonal transitional maximum of precipitation in the same region in boreal spring, exhibited as a weak doublemore » ITCZ pattern in the equatorial eastern Pacific. This climatological seasonal variation, however, varies greatly from year to year: double ITCZ in the boreal spring occurs in some years but not in other years; when there a single ITCZ, it can appear either north, south or at the equator. Understanding this observed variability is critical to find the ultimate cause of the double ITCZ in climate models. Seasonal variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have found that in the region where spurious ITCZ in models occurs, there is a “seasonal cloud transition” — from stratocumulus to shallow cumulus and eventually to deep convection —in the South Equatorial Pacific (SEP) from September to April that is similar to the spatial cloud transition from the California coast to the equator. This seasonal transition is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence. This finding of seasonal cloud transition points to the same source of model errors in the ITCZ simulations as in simulation of stratocumulus-cumulus-deep convection transition. It provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double Inter-tropical Convergence Zone (ITCZ) in most models. This work is recently published in Yu et al. (2016). Interannual variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have characterized the interannual variation of boreal spring precipitation in the eastern tropical Pacific and found the cause of the observed interannual variability. We have shown that ITCZ in this region can occur as a single ITCZ along the Equator, single ITCZ north of the Equator, single ITCZ south of the Equator, and double ITCZ on both sides of the Equator. We have found that convective instability only plays a secondary role in the ITCZ interannual variability. Instead, the remote impact of the Pacific basin-wide SST on the horizontal gradient of surface pressure and wind convergence is the primary driver of this interannual variability. Results point to the need to include moisture convergence in convection schemes to improve the simulation of precipitation in the eastern tropical Pacific. This result has been recently submitted for publication (Yu and Zhang 2016). 2. Improvement of model parameterizations to reduce the double ITCZ bias We analyzed the current status of climate model performance in simulating precipitation in the equatorial Pacific. We have found that the double ITCZ bias has not been reduced in CMIP5 models relative to CMIP4 models. We have characterized the dynamic structure of the common bias by using precipitation, sea surface temperature, surface winds and sea-level. Results are published in Zhang et al. (2015): Since cumulus convection plays a significant role in the double ITCZ behavior in models, we have used measurements from ARM and other sources to carry out a systematic analysis of the roles of shallow and deep convection in the CAM. We found that in both CAM4 and CAM5, when the intensity of deep convection decreases as a result of parameterization change, the intensity of shallow convection increases, leading to very different changes in precipitation partitions but little change in the total precipitation. The different precipitation partition however can manifest themselves in other measures of model performances including temperature and humidity. This study points to the need to treat model physical parameterizations as integrated system rather than individual components. Results from this study are published in Wang and Zhang (2013). Since shallow convection interacts with the deep convection scheme and surface turbulence to trigger the double ITCZ, we studied methods to improve the shallow convection scheme in climate models. We investigated the bulk budgets of the vertical velocity and its parameterization in convective cores, convective updrafts, and clouds by using large-eddy simulation (LES) of four shallow convection cases including one from ARM. We proposed optimal forms of the Simpson and Wiggert equation to calculate the vertical velocity in bulk mass flux convection schemes for convective cores, convective updrafts, and convective clouds as parameterization schemes. The new scheme is published in Wang and Zhang (2014). By using long-term radar-based ground measurements from ARM, we derived a scale-aware inhomogeneity parameterization of cloud liquid water in climate models. We found a relationship between the inhomogeneity parameter and the model grid size as well as atmospheric stability. This relationship is implemented in the CESM to describe the subgrid-scale cloud inhomogeneity. Relative to the default CESM with the finite-volume dynamic core at 2-degree resolution, the new parameterization leads to smaller cloud inhomogeneity and larger cloud liquid-water path in high latitudes, and the opposite effect in low latitudes, with the regional impact on shortwave cloud radiation effect of up to 10 W/m 2. This is due to both the smaller (larger) grid size in high (low) latitudes in the longitude-latitude grid setting of CESM and the more stable (unstable) atmosphere. This parameterization is expected lead to more realistic simulation of tropical precipitation in high-resolution models. Results from this study are reported in Xie and Zhang (2015).« less

Comparison of Gravity Wave Temperature Variances from Ray-Based Spectral Parameterization of Convective Gravity Wave Drag with AIRS Observations

NASA Technical Reports Server (NTRS)

Choi, Hyun-Joo; Chun, Hye-Yeong; Gong, Jie; Wu, Dong L.

2012-01-01

The realism of ray-based spectral parameterization of convective gravity wave drag, which considers the updated moving speed of the convective source and multiple wave propagation directions, is tested against the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite. Offline parameterization calculations are performed using the global reanalysis data for January and July 2005, and gravity wave temperature variances (GWTVs) are calculated at z = 2.5 hPa (unfiltered GWTV). AIRS-filtered GWTV, which is directly compared with AIRS, is calculated by applying the AIRS visibility function to the unfiltered GWTV. A comparison between the parameterization calculations and AIRS observations shows that the spatial distribution of the AIRS-filtered GWTV agrees well with that of the AIRS GWTV. However, the magnitude of the AIRS-filtered GWTV is smaller than that of the AIRS GWTV. When an additional cloud top gravity wave momentum flux spectrum with longer horizontal wavelength components that were obtained from the mesoscale simulations is included in the parameterization, both the magnitude and spatial distribution of the AIRS-filtered GWTVs from the parameterization are in good agreement with those of the AIRS GWTVs. The AIRS GWTV can be reproduced reasonably well by the parameterization not only with multiple wave propagation directions but also with two wave propagation directions of 45 degrees (northeast-southwest) and 135 degrees (northwest-southeast), which are optimally chosen for computational efficiency.

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.

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shi, J.; Chen, S. S> ; Lang, S.; Hong, S.-Y.; Thompson, G.; Peters-Lidard, C.; Hou, A.; Braun, S.;

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes

NASA Astrophysics Data System (ADS)

Huang, Y. C.; Wang, P. K.

2017-12-01

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes Yi-Chih Huang and Pao K. Wang Ice particles contribute to the microphysics and dynamics of severe storms in various regions of the world to a degree that is not commonly recognized. This study is motivated by the need to understand the role of ice particles plays in the development of severe storms so that their impact on various aspects of the storm behavior can be properly assessed. In this study, we perform numerical simulations of thunderstorms using a cloud resolving model WISCDYMM that includes parameterized microphysical processes to understand the role played by ice processes. We simulate thunderstorms occurred over various regions of the world including tropics, substropics and midlatitudes. We then perform statistical analysis of the simulated results to show the formation of various categories of hydrometeors to reveal the importance of ice processes. We will show that ice hydrometeors (cloud ice, snow, graupel/hail) account for 80% of the total hydrometeor mass for the High Plains storms but 50% for the subtropical storms. In addition, the melting of large ice particles (graupel and hail) is the major production process of rain in tropical storms although the ratio of ice-phase mass is responsible for only 40% of the total hydrometeor mass. Furthermore, hydrometeors have their own special microphysical processes in development and depletion over various latitudes. Microphysical structures depend on atmospheric dynamical and thermodynamical conditions which determine the partitioning of hydrometeors. This knowledge would benefit the microphysics parameterization in cloud models and cumulus parameterization in global circulation models.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Parameterization of bulk condensation in numerical cloud models

NASA Technical Reports Server (NTRS)

Kogan, Yefim L.; Martin, William J.

1994-01-01

The accuracy of the moist saturation adjustment scheme has been evaluated using a three-dimensional explicit microphysical cloud model. It was found that the error in saturation adjustment depends strongly on the Cloud Condensation Nucleii (CCN) concentration in the ambient atmosphere. The scheme provides rather accurate results in the case where a sufficiently large number of CCN (on the order of several hundred per cubic centimeter) is available. However, under conditions typical of marine stratocumulus cloud layers with low CCN concentration, the error in the amounts of condensed water vapor and released latent heat may be as large as 40%-50%. A revision of the saturation adjustment scheme is devised that employs the CCN concentration, dynamical supersaturation, and cloud water content as additional variables in the calculation of the condensation rate. The revised condensation model reduced the error in maximum updraft and cloud water content in the climatically significant case of marine stratocumulus cloud layers by an order of magnitude.

Relationships between lower tropospheric stability, low cloud cover, and water vapor isotopic composition in the subtropical Pacific

NASA Astrophysics Data System (ADS)

Galewsky, J.

2017-12-01

Understanding the processes that govern the relationships between lower tropospheric stability and low-cloud cover is crucial for improved constraints on low-cloud feedbacks and for improving the parameterizations of low-cloud cover used in climate models. The stable isotopic composition of atmospheric water vapor is a sensitive recorder of the balance of moistening and drying processes that set the humidity of the lower troposphere and may thus provide a useful framework for improving our understanding low-cloud processes. In-situ measurements of water vapor isotopic composition collected at the NOAA Mauna Loa Observatory in Hawaii, along with twice-daily soundings from Hilo and remote sensing of cloud cover, show a clear inverse relationship between the estimated inversion strength (EIS) and the mixing ratios and water vapor δ -values, and a positive relationship between EIS, deuterium excess, and Δ δ D, defined as the difference between an observation and a reference Rayleigh distillation curve. These relationships are consistent with reduced moistening and an enhanced upper-tropospheric contribution above the trade inversion under high EIS conditions and stronger moistening under weaker EIS conditions. The cloud fraction, cloud liquid water path, and cloud-top pressure were all found to be higher under low EIS conditions. Inverse modeling of the isotopic data for the highest and lowest terciles of EIS conditions provide quantitative constraints on the cold-point temperatures and mixing fractions that govern the humidity above the trade inversion. The modeling shows the moistening fraction between moist boundary layer air and dry middle tropospheric air 24±1.5% under low EIS conditions is and 6±1.5% under high EIS conditions. A cold-point (last-saturation) temperature of -30C can match the observations for both low and high EIS conditions. The isotopic composition of the moistening source as derived from the inversion (-114±10‰ ) requires moderate fractionation from a pure marine source, indicating a link between inversion strength and moistening of the lower troposphere from the outflow of shallow convection. This approach can be applied in other settings and the results can be used to test parameterizations in climate models.

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

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

Gettelman, A.; Liu, Xiaohong; Ghan, Steven J.

2010-09-28

A process-based treatment of ice supersaturation and ice-nucleation is implemented in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). The new scheme is designed to allow (1) supersaturation with respect to ice, (2) ice nucleation by aerosol particles and (3) ice cloud cover consistent with ice microphysics. The scheme is implemented with a 4-class 2 moment microphysics code and is used to evaluate ice cloud nucleation mechanisms and supersaturation in CAM. The new model is able to reproduce field observations of ice mass and mixed phase cloud occurrence better than previous versions of the model. Simulations indicatemore » heterogeneous freezing and contact nucleation on dust are both potentially important over remote areas of the Arctic. Cloud forcing and hence climate is sensitive to different formulations of the ice microphysics. Arctic radiative fluxes are sensitive to the parameterization of ice clouds. These results indicate that ice clouds are potentially an important part of understanding cloud forcing and potential cloud feedbacks, particularly in the Arctic.« less

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

Parameterizations of the Vertical Variability of Tropical Cirrus Cloud Microphysical and Optical Properties

NASA Technical Reports Server (NTRS)

Twohy, Cynthia; Heymsfield, Andrew; Gerber, Hermann

2005-01-01

Our multi-investigator effort was targeted at the following areas of interest to CRYSTAL-FACE: (1) the water budgets of anvils, (2) parameterizations of the particle size distributions and related microphysical and optical properties (3) characterizations of the primary ice particle habits, (4) the relationship of the optical properties to the microphysics and particle habits, and (5) investigation of the ice-nuclei types and mechanisms in anvil cirrus. Dr. Twohy's effort focused on (l), (2), and (5), with the measurement and analysis of ice water content and cirrus residual nuclei using the counterflow virtual impactor (CVI).

Numerical experiments on the role of radiative processes in the development and maintenance of upper level clouds

NASA Technical Reports Server (NTRS)

Starr, D. O'C.; Cox, S. K.

1981-01-01

A time-dependent, two-dimensional Eulerian model is presented whose purpose is to obtain more realistic parameterizations of extended high level cloudiness, and the results of a numerical experiment using the model are reported. The model is anelastic and the Bousinesque assumption is invoked. Unresolved subgrid scale processes are parameterized as eddy diffusion processes. Two phases of water are incorporated and equilibrium between them is assumed. The effects of infrared radiative processes are parametrically represented. Two simulations were conducted with identical initial conditions; in one of them, the radiation term was never turned on. The mean values of perturbation potential temperature at each level in the domain are plotted versus height after 15, 30, and 60 minutes of simulated time. The influence of the radiative term is seen to impose a cooling trend, leading to an increased generation of ice water and an increased generation of turbulent kinetic energy in the cloud layer.

Short-term Time Step Convergence in a Climate Model

DOE PAGES

Wan, Hui; Rasch, Philip J.; Taylor, Mark; ...

2015-02-11

A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore » expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less

Investigation of tropical diurnal convection biases in a climate model using TWP-ICE observations and convection-permitting simulations

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Jackson, R. C.; Endo, S.; Vogelmann, A. M.; Collis, S. M.; Golaz, J. C.

2017-12-01

Climate models are known to have difficulty in simulating tropical diurnal convections that exhibit distinct characteristics over land and open ocean. While the causes are rooted in deficiencies in convective parameterization in general, lack of representations of mesoscale dynamics in terms of land-sea breeze, convective organization, and propagation of convection-induced gravity waves also play critical roles. In this study, the problem is investigated at the process-level with the U.S. Department of Energy Accelerated Climate Modeling for Energy (ACME) model in short-term hindcast mode using the Cloud Associated Parameterization Testbed (CAPT) framework. Convective-scale radar retrievals and observation-driven convection-permitting simulations for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) cases are used to guide the analysis of the underlying processes. The emphasis will be on linking deficiencies in representation of detailed process elements to the model biases in diurnal convective properties and their contrast among inland, coastal and open ocean conditions.

Parameterization of Photon Tunneling with Application to Ice Cloud Optical Properties at Terrestrial Wavelengths

NASA Astrophysics Data System (ADS)

Mitchell, D. L.

2006-12-01

Sometimes deep physical insights can be gained through the comparison of two theories of light scattering. Comparing van de Hulst's anomalous diffraction approximation (ADA) with Mie theory yielded insights on the behavior of the photon tunneling process that resulted in the modified anomalous diffraction approximation (MADA). (Tunneling is the process by which radiation just beyond a particle's physical cross-section may undergo large angle diffraction or absorption, contributing up to 40% of the absorption when wavelength and particle size are comparable.) Although this provided a means of parameterizing the tunneling process in terms of the real index of refraction and size parameter, it did not predict the efficiency of the tunneling process, where an efficiency of 100% is predicted for spheres by Mie theory. This tunneling efficiency, Tf, depends on particle shape and ranges from 0 to 1.0, with 1.0 corresponding to spheres. Similarly, by comparing absorption efficiencies predicted by the Finite Difference Time Domain Method (FDTD) with efficiencies predicted by MADA, Tf was determined for nine different ice particle shapes, including aggregates. This comparison confirmed that Tf is a strong function of ice crystal shape, including the aspect ratio when applicable. Tf was lowest (< 0.36) for aggregates and plates, and largest (> 0.9) for quasi- spherical shapes. A parameterization of Tf was developed in terms of (1) ice particle shape and (2) mean particle size regarding the large mode (D > 70 mm) of the ice particle size distribution. For the small mode, Tf is only a function of ice particle shape. When this Tf parameterization is used in MADA, absorption and extinction efficiency differences between MADA and FDTD are within 14% over the terrestrial wavelength range 3-100 mm for all size distributions and most crystal shapes likely to be found in cirrus clouds. Using hyperspectral radiances, it is demonstrated that Tf can be retrieved from ice clouds. Since Tf is a function of ice particle shape, this may provide a means of retrieving qualitative information on ice particle shape.

Applying an economical scale-aware PDF-based turbulence closure model in NOAA NCEP GCMs.

NASA Astrophysics Data System (ADS)

Belochitski, A.; Krueger, S. K.; Moorthi, S.; Bogenschutz, P.; Cheng, A.

2017-12-01

A novel unified representation of sub-grid scale (SGS) turbulence, cloudiness, and shallow convection is being implemented into the NOAA NCEP Global Forecasting System (GFS) general circulation model. The approach, known as Simplified High Order Closure (SHOC), is based on predicting a joint PDF of SGS thermodynamic variables and vertical velocity, and using it to diagnose turbulent diffusion coefficients, SGS fluxes, condensation, and cloudiness. Unlike other similar methods, comparatively few new prognostic variables needs to be introduced, making the technique computationally efficient. In the base version of SHOC it is SGS turbulent kinetic energy (TKE), and in the developmental version — SGS TKE, and variances of total water and moist static energy (MSE). SHOC is now incorporated into a version of GFS that will become a part of the NOAA Next Generation Global Prediction System based around NOAA GFDL's FV3 dynamical core, NOAA Environmental Modeling System (NEMS) coupled modeling infrastructure software, and a set novel physical parameterizations. Turbulent diffusion coefficients computed by SHOC are now used in place of those produced by the boundary layer turbulence and shallow convection parameterizations. Large scale microphysics scheme is no longer used to calculate cloud fraction or the large-scale condensation/deposition. Instead, SHOC provides these quantities. Radiative transfer parameterization uses cloudiness computed by SHOC. An outstanding problem with implementation of SHOC in the NCEP global models is excessively large high level tropical cloudiness. Comparison of the moments of the SGS PDF diagnosed by SHOC to the moments calculated in a GigaLES simulation of tropical deep convection case (GATE), shows that SHOC diagnoses too narrow PDF distributions of total cloud water and MSE in the areas of deep convective detrainment. A subsequent sensitivity study of SHOC's diagnosed cloud fraction (CF) to higher order input moments of the SGS PDF demonstrated that CF is improved if SHOC is provided with correct variances of total water and MSE. Consequently, SHOC was modified to include two new prognostic equations for variances of total water and MSE, and coupled with the Chikira-Sugiyama parameterization of deep convection to include effects of detrainment on the prognostic variances.

Implication of observed cloud variability for parameterizations of microphysical and radiative transfer processes in climate models

NASA Astrophysics Data System (ADS)

Huang, D.; Liu, Y.

2014-12-01

The effects of subgrid cloud variability on grid-average microphysical rates and radiative fluxes are examined by use of long-term retrieval products at the Tropical West Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy's Atmospheric Radiation Measurement (ARM) Program. Four commonly used distribution functions, the truncated Gaussian, Gamma, lognormal, and Weibull distributions, are constrained to have the same mean and standard deviation as observed cloud liquid water content. The PDFs are then used to upscale relevant physical processes to obtain grid-average process rates. It is found that the truncated Gaussian representation results in up to 30% mean bias in autoconversion rate whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest and thus there is no single distribution function that works best for all parameterizations. Examination of the scale (window size) dependence of the mean bias indicates that the bias in grid-average process rates monotonically increases with increasing window sizes, suggesting the increasing importance of subgrid variability with increasing grid sizes.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

A Method to Analyze How Various Parts of Clouds Influence Each Other's Brightness

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William (Technical Monitor)

2001-01-01

This paper proposes a method for obtaining new information on 3D radiative effects that arise from horizontal radiative interactions in heterogeneous clouds. Unlike current radiative transfer models, it can not only calculate how 3D effects change radiative quantities at any given point, but can also determine which areas contribute to these 3D effects, to what degree, and through what mechanisms. After describing the proposed method, the paper illustrates its new capabilities both for detailed case studies and for the statistical processing of large datasets. Because the proposed method makes it possible, for the first time, to link a particular change in cloud properties to the resulting 3D effect, in future studies it can be used to develop new radiative transfer parameterizations that would consider 3D effects in practical applications currently limited to 1D theory-such as remote sensing of cloud properties and dynamical cloud modeling.

Sensitivity of aerosol indirect forcing and autoconversion to cloud droplet parameterization: an assessment with the NASA Global Modeling Initiative.

NASA Astrophysics Data System (ADS)

Sotiropoulou, R. P.; Meshkhidze, N.; Nenes, A.

2006-12-01

The aerosol indirect forcing is one of the largest sources of uncertainty in assessments of anthropogenic climate change [IPCC, 2001]. Much of this uncertainty arises from the approach used for linking cloud droplet number concentration (CDNC) to precursor aerosol. Global Climate Models (GCM) use a wide range of cloud droplet activation mechanisms ranging from empirical [Boucher and Lohmann, 1995] to detailed physically- based formulations [e.g., Abdul-Razzak and Ghan, 2000; Fountoukis and Nenes, 2005]. The objective of this study is to assess the uncertainties in indirect forcing and autoconversion of cloud water to rain caused by the application of different cloud droplet parameterization mechanisms; this is an important step towards constraining the aerosol indirect effects (AIE). Here we estimate the uncertainty in indirect forcing and autoconversion rate using the NASA Global Model Initiative (GMI). The GMI allows easy interchange of meteorological fields, chemical mechanisms and the aerosol microphysical packages. Therefore, it is an ideal tool for assessing the effect of different parameters on aerosol indirect forcing. The aerosol module includes primary emissions, chemical production of sulfate in clear air and in-cloud aqueous phase, gravitational sedimentation, dry deposition, wet scavenging in and below clouds, and hygroscopic growth. Model inputs include SO2 (fossil fuel and natural), black carbon (BC), organic carbon (OC), mineral dust and sea salt. The meteorological data used in this work were taken from the NASA Data Assimilation Office (DAO) and two different GCMs: the NASA GEOS4 finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II' (GISS II') GCM. Simulations were carried out for "present day" and "preindustrial" emissions using different meteorological fields (i.e. DAO, FVGCM, GISS II'); cloud droplet number concentration is computed from the correlations of Boucher and Lohmann [1995], Abdul-Razzak and Ghan [2000], Feingold and Heymsfield [1992], Fountoukis and Nenes [2005] and Segal and Khain [2006]. Computed CDNC is used to calculate the cloud optical depth, the autoconversion rate and the mean top-of-the-atmosphere (TOA) short-wave radiative forcing using modified FAST-J algorithm [Meshkhidze et al., 2006]. Autoconversion of cloud water to precipitation is parameterized following the formulation of Khairoutdinov and Kogan [2000]. References Abdul-Razzak, H., and S. J. Ghan (2000), J. Geophys. Res., 105, 6837-6844. Boucher, O., and U. Lohmann (1995), Tellus, Ser. B, 47, 281- 300. Feingold, G. and A. Heymsfield (1992), J. Atmos. Sci., 49, 2325-2342. Fountoukis, C., and A. Nenes (2005), J. Geophys. Res., 110, D11212, doi:10.1029/ 2004JD005591. Intergovernmental Panel on Climate Change - IPCC (2001), Climate Change, The Scientific Basis, Cambridge University Press, UK. Khairoutdinov, M. and Y. Kogan (2000), Mon. Weather Rev., 128 (1), 229-243. Meshkhidze, N., A Nenes, J. Kouatchou, B. Das and J. Rodriguez, 7th International Aerosol Conference, American Association for Aerosol Research (IAC 2006), St. Paul, Minnesota, October 2006 Nenes, A., and J. H. Seinfeld (2003), J. Geophys. Res., 108, 4415, doi:10.1029/ 2002JD002911. Segal, Y., and A. Khain (2006), J. Geophys. Res., 111, D15204, doi:10.1029/2005JD006561.

A Generalized Simple Formulation of Convective Adjustment ...

EPA Pesticide Factsheets

Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a prescribed value or ad hoc representation of τ is used in most global and regional climate/weather models making it a tunable parameter and yet still resulting in uncertainties in convective precipitation simulations. In this work, a generalized simple formulation of τ for use in any convection parameterization for shallow and deep clouds is developed to reduce convective precipitation biases at different grid spacing. Unlike existing other methods, our new formulation can be used with field campaign measurements to estimate τ as demonstrated by using data from two different special field campaigns. Then, we implemented our formulation into a regional model (WRF) for testing and evaluation. Results indicate that our simple τ formulation can give realistic temporal and spatial variations of τ across continental U.S. as well as grid-scale and subgrid scale precipitation. We also found that as the grid spacing decreases (e.g., from 36 to 4-km grid spacing), grid-scale precipitation dominants over subgrid-scale precipitation. The generalized τ formulation works for various types of atmospheric conditions (e.g., continental clouds due to heating and large-scale forcing over la

Investigation of the effects of the macrophysical and microphysical properties of cirrus clouds on the retrieval of optical properties: Results for FIRE 2

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Stephens, Graeme L.

1993-01-01

Due to the prevalence and persistence of cirrus cloudiness across the globe, cirrus clouds are believed to have an important effect on the climate. Stephens et al., (1990) among others have shown that the important factor determining how cirrus clouds modulate the climate is the balance between the albedo and emittance effect of the cloud systems. This factor was shown to depend in part upon the effective sizes of the cirrus cloud particles. Since effective sizes of cirrus cloud microphysical distributions are used as a basis of parameterizations in climate models, it is crucial that the relationships between effective sizes and radiative properties be clearly established. In this preliminary study, the retrieval of cirrus cloud effective sizes are examined using a two dimensional radiative transfer model for a cirrus cloud case sampled during FIRE Cirrus 11. The purpose of this paper is to present preliminary results from the SHSG model demonstrating the sensitivity of the bispectral relationships of reflected radiances and thus the retrieval of effective sizes to phase function and dimensionality.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.

Development of a Cloud Resolving Model for Heterogeneous Supercomputers

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

COSP: Satellite simulation software for model assessment

DOE PAGES

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

2011-08-01

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

The FIRE Cirrus Science Results 1993

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1993-01-01

FIRE (First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment) is a U.S. cloud-radiation research program that seeks to improve our basic understanding and parameterizations of cirrus and marine stratocumulus cloud systems and ISCCP data products. The FIRE Cirrus Science Conference was held in Breckenridge, CO, 14-17 Jun. 1993, to present results of cirrus research for the second phase of FIRE (1989-present) and to refine cirrus research goals and priorities for the next phase of FIRE (1994-future). This Conference Publication contains the text of short papers presented at the conference. The papers describe research analyses of data collected at the Cirrus Intensive Field Observations-2 field experiment conducted in Kansas, 13 Nov. - 7 Dec. 1991.

Tropical Cloud Properties and Radiative Heating Profiles

DOE Data Explorer

Mather, James

2008-01-15

We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

NASA Technical Reports Server (NTRS)

Kawamoto, K.; Minnis, P.; Arduini, R.; Smith, W., Jr.

2001-01-01

Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

Sensitivity of Pacific Cold Tongue and Double-ITCZ Bias to Convective Parameterization

NASA Astrophysics Data System (ADS)

Woelfle, M.; Bretherton, C. S.; Pritchard, M. S.; Yu, S.

2016-12-01

Many global climate models struggle to accurately simulate annual mean precipitation and sea surface temperature (SST) fields in the tropical Pacific basin. Precipitation biases are dominated by the double intertropical convergence zone (ITCZ) bias where models exhibit precipitation maxima straddling the equator while only a single Northern Hemispheric maximum exists in observations. The major SST bias is the enhancement of the equatorial cold tongue. A series of coupled model simulations are used to investigate the sensitivity of the bias development to convective parameterization. Model components are initialized independently prior to coupling to allow analysis of the transient response of the system directly following coupling. These experiments show precipitation and SST patterns to be highly sensitive to convective parameterization. Simulations in which the deep convective parameterization is disabled forcing all convection to be resolved by the shallow convection parameterization showed a degradation in both the cold tongue and double-ITCZ biases as precipitation becomes focused into off-equatorial regions of local SST maxima. Simulations using superparameterization in place of traditional cloud parameterizations showed a reduced cold tongue bias at the expense of additional precipitation biases. The equatorial SST responses to changes in convective parameterization are driven by changes in near equatorial zonal wind stress. The sensitivity of convection to SST is important in determining the precipitation and wind stress fields. However, differences in convective momentum transport also play a role. While no significant improvement is seen in these simulations of the double-ITCZ, the system's sensitivity to these changes reaffirm that improved convective parameterizations may provide an avenue for improving simulations of tropical Pacific precipitation and SST.

New Parameterizations for Neutral and Ion-Induced Sulfuric Acid-Water Particle Formation in Nucleation and Kinetic Regimes

NASA Astrophysics Data System (ADS)

Määttänen, Anni; Merikanto, Joonas; Henschel, Henning; Duplissy, Jonathan; Makkonen, Risto; Ortega, Ismael K.; Vehkamäki, Hanna

2018-01-01

We have developed new parameterizations of electrically neutral homogeneous and ion-induced sulfuric acid-water particle formation for large ranges of environmental conditions, based on an improved model that has been validated against a particle formation rate data set produced by Cosmics Leaving OUtdoor Droplets (CLOUD) experiments at European Organization for Nuclear Research (CERN). The model uses a thermodynamically consistent version of the Classical Nucleation Theory normalized using quantum chemical data. Unlike the earlier parameterizations for H2SO4-H2O nucleation, the model is applicable to extreme dry conditions where the one-component sulfuric acid limit is approached. Parameterizations are presented for the critical cluster sulfuric acid mole fraction, the critical cluster radius, the total number of molecules in the critical cluster, and the particle formation rate. If the critical cluster contains only one sulfuric acid molecule, a simple formula for kinetic particle formation can be used: this threshold has also been parameterized. The parameterization for electrically neutral particle formation is valid for the following ranges: temperatures 165-400 K, sulfuric acid concentrations 104-1013 cm-3, and relative humidities 0.001-100%. The ion-induced particle formation parameterization is valid for temperatures 195-400 K, sulfuric acid concentrations 104-1016 cm-3, and relative humidities 10-5-100%. The new parameterizations are thus applicable for the full range of conditions in the Earth's atmosphere relevant for binary sulfuric acid-water particle formation, including both tropospheric and stratospheric conditions. They are also suitable for describing particle formation in the atmosphere of Venus.

An assessment of the cloud signals simulated by NICAM using ISCCP, CALIPSO, and CloudSat satellite simulators

NASA Astrophysics Data System (ADS)

Kodama, C.; Noda, A. T.; Satoh, M.

2012-06-01

This study presents an assessment of three-dimensional structures of hydrometeors simulated by the NICAM, global nonhydrostatic atmospheric model without cumulus parameterization, using multiple satellite data sets. A satellite simulator package (COSP: the CFMIP Observation Simulator Package) is employed to consistently compare model output with ISCCP, CALIPSO, and CloudSat satellite observations. Special focus is placed on high thin clouds, which are not observable in the conventional ISCCP data set, but can be detected by the CALIPSO observations. For the control run, the NICAM simulation qualitatively captures the geographical distributions of the high, middle, and low clouds, even though the horizontal mesh spacing is as coarse as 14 km. The simulated low cloud is very close to that of the CALIPSO low cloud. Both the CloudSat observations and NICAM simulation show a boomerang-type pattern in the radar reflectivity-height histogram, suggesting that NICAM realistically simulates the deep cloud development process. A striking difference was found in the comparisons of high thin cirrus, showing overestimated cloud and higher cloud top in the model simulation. Several model sensitivity experiments are conducted with different cloud microphysical parameters to reduce the model-observation discrepancies in high thin cirrus. In addition, relationships among clouds, Hadley circulation, outgoing longwave radiation and precipitation are discussed through the sensitivity experiments.

One-dimensional numerical modeling of Blue Jet and its impact on stratospheric chemistry

NASA Astrophysics Data System (ADS)

Duruisseau, F.; Thiéblemont, R.; Huret, N.

2011-12-01

In the stratosphere the ozone layer is very sensitive to the NOx abundance. The ionisation of N2 and O2 molecules by TLE's (Transient Luminous Events) is a source of NOx which is currently not well quantified and could act as a loss of ozone. In this study a one dimensional explicit parameterization of a Blue-Jet propagation based on that proposed by Raizer et al. (2006 and 2007) has been developed. This parameterization considers Blue-Jet as a streamer initiated by a bidirectional leader discharge, emerging from the anvil and sustained by moderate cloud charge. The streamer growth varies with the electrical field induced by initial cloud charge and the initial altitude. This electrical parameterization and the chemical mechanisms associated with the discharge have been implemented into a detailed chemical model of stratospheric ozone including evolution of nitrogen, chlorine and bromine species. We will present several tests performed to validate the electrical code and evaluate the propagation velocity and the maximum altitude attains by the blue jet as a function of electrical parameters. The results obtained giving the spatiotemporal evolution of the electron density are then used to initiate the specific chemistry associated with the Blue Jet. Preliminary results on the impact of such discharge on the ozone content and the whole stratospheric system will be presented.

Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

NASA Astrophysics Data System (ADS)

Bergot, Thierry

2007-06-01

Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog appears in the surface boundary layer and is driven by the interactions between land surface and the lower layers of the atmosphere. These interactions are still not well parameterized in current operational NWP models, and a new methodology based on local observations, an adaptive assimilation scheme and a local numerical model is tested. The proposed numerical forecast method of foggy conditions has been run during three years at Paris-CdG international airport. This test over a long-time period allows an in-depth evaluation of the forecast quality. This study demonstrates that detailed 1-D models, including detailed physical parameterizations and high vertical resolution, can reasonably represent the major features of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset and burn-off time is typically 1 h. The major weakness of the methodology is related to the evolution of low clouds (stratus lowering). Even if the occurrence of fog is well forecasted, the value of the horizontal visibility is only crudely forecasted. Improvements in the microphysical parameterization and in the translation algorithm converting NWP prognostic variables into a corresponding horizontal visibility seems necessary to accurately forecast the value of the visibility.

Revised cloud processes to improve the mean and intraseasonal variability of Indian summer monsoon in climate forecast system: Part 1

NASA Astrophysics Data System (ADS)

Abhik, S.; Krishna, R. P. M.; Mahakur, M.; Ganai, Malay; Mukhopadhyay, P.; Dudhia, J.

2017-06-01

The National Centre for Environmental Prediction (NCEP) Climate Forecast System (CFS) is being used for operational monsoon prediction over the Indian region. Recent studies indicate that the moist convective process in CFS is one of the major sources of uncertainty in monsoon predictions. In this study, the existing simple cloud microphysics of CFS is replaced by the six-class Weather Research Forecasting (WRF) single moment (WSM6) microphysical scheme. Additionally, a revised convective parameterization is employed to improve the performance of the model in simulating the boreal summer mean climate and intraseasonal variability over the Indian summer monsoon (ISM) region. The revised version of the model (CFSCR) exhibits a potential to improve shortcomings in the seasonal mean precipitation distribution relative to the standard CFS (CTRL), especially over the ISM region. Consistently, notable improvements are also evident in other observed ISM characteristics. These improvements are found to be associated with a better simulation of spatial and vertical distributions of cloud hydrometeors in CFSCR. A reasonable representation of the subgrid-scale convective parameterization along with cloud hydrometeors helps to improve the convective and large-scale precipitation distribution in the model. As a consequence, the simulated low-frequency boreal summer intraseasonal oscillation (BSISO) exhibits realistic propagation and the observed northwest-southeast rainband is well reproduced in CFSCR. Additionally, both the high and low-frequency BSISOs are better captured in CFSCR. The improvement of low and high-frequency BSISOs in CFSCR is shown to be related to a realistic phase relationship of clouds.