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At least 163 records · Page 9

Advancements in the Representation of Cloud-Aerosol Microphysics in the GEOS-5 AGCM

Despite numerous challenges, the physical parameterization of cloud-aerosol interactions in atmospheric GCMs has become a top priority for advancement because of our need to simulate and understand past, current, and future indirect effects of aerosols on clouds. The challenges stem from the involvement of wide range of cloud-scale dynamics and aerosol activation physical processes. Cloud dynamics modulate cloud areal extent and condensate, while aerosol activation depends on aerosol mass load, size distribution, internal mixing state, and nucleating properties, and ultimately determines cloud optical properties via particle sizes. Both macro- and micro-scale processes are obviously important for cloud-radiation interactions. We will present the main features of cloud microphysical properties in the GEOS- 5 Atmospheric GCM (AGCM) as simulated by the McRAS-AC (Microphysics of Clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction) scheme. McRAS-AC uses Fountoukis and Nenes (2005) aerosol activation for liquid clouds, and has an option for either Liu and Penner (2005) or Barahona and Nenes (2008, 2009) aerosol activation for ice clouds. Aerosol loading (on-line or climatological) comes from GOCART, with an assumed log-normal size distribution. Other features of McRAS-AC are level-by-level cloud-scale thermodynamics, and Seifert-Beheng (2001)-type precipitation microphysics, particularly from moist convection. Results from Single-Column Model simulations will be shown to demonstrate how cloud radiative properties, lifetimes, and precipitation are influenced by different parameterization assumptions. Corresponding fields from year-long simulations of the full AGCM will also be presented with geographical distributions of cloud effective particle sizes compared to satellite retrievals. While the primary emphasis will be on current climate, simulation results with perturbed aerosol loadings will also be shown to expose the radiative sensitivity of the microphysical parameterization.

Lee, D.↗

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

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.

clouds↗

Configuration and Assessment of the GISS ModelE2 Contributions to the CMIP5 Archive

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

ocean model↗

Reflectivities of uniform and broken stratiform clouds: An update

The reflectivities of uniform and broken stratiform clouds obtained from the NOAA-9 and NOAA-10 overpasses collected during the FIRE Marine Stratocumulus Intensive Field Observations (IFO) were compared, and these reflectivities were compared with those obtained through radiative transfer calculation performed for plane-parallel cloud models. The objective was to determine the extent to which plane-parallel radiative transfer calculations could reproduce the reflectivities observed for uniform clouds and to determine the extent to which finite cloud effects cause broken clouds to reflect differently than uniform clouds. The latter study is to provide guidance in the parameterization of finite cloud effects in general circulation climate models as well as to assess the ability of plane-parallel theory, which is used by ISCCP to retrieve cloud properties, to treat the reflectivities of broken clouds. Some results from this study were reported at the last FIRE Science Team meeting and some were reported elsewhere (Coakley and Briegleb, 1989). Improvements since the previous reports include: (1) the analysis of additional satellite passes, and (2) a modification to the analysis which helps to show the significance of the differences in reflectivities for uniform and broken clouds.

Coakley, James A., Jr.↗

Response of cumulus clouds to large-scale forcing and cumulus parameterization

Using the cumulus ensemble model (Soong and Ogura, 1980), statistical properties of cumulus clouds that occur in response to the imposed large scale forcing were investigated both in the tropical and midlatitude situtations. A strong drying process was found to occur in the boundary layer in association with deep convection in a midlatitude case. The Arakawa-Schubert (1974) cumulus parameterization scheme was tested semi-prognostically against both the model result and the observation in a tropical rain event that occurred in GATE. The Cloud heating and drying effects predicted by the Arakawa-Schubert scheme were found to agree well both with the observation and the model result. However, it was also found that the Arakawa-Schuber scheme underestimates both condensation and evaporation rates substantially. An inclusion of the downdraft effect, as formulated by Johnson (1976), appears to alleviate this deficiency. This downdraft effect may be important in predicting the behavior of the boundary accurately.

Ogura, Y.↗

Stochastic Convection Parameterizations

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

atmospheric models↗

Facility for Atmospheric Remote Sensing (FARS) Cirrus Measurements for FIRE III

From our Facility of Atmospheric Remote Sensing (FARS) in Salt Lake City, Utah, we have since December 1986 collected ground-truth data from cirrus clouds for aiding in satellite cloud detection algorithm testing and improvement, the development of cirrus radiative parameterizations, and basic cloud physics research. This research program has involved data regularly collected with a polarization ruby (0.694 micrometer) lidar system and a suit of passive (visible, infrared, and microwave) radiometers, although a number of comprehensive cloud case studies using the full compliment of remote sensors (i.e., 95 GHz polarimetric Doppler radar and high-resolution dual-wavelength Polarization Diversity Lidar, PDL) have also been obtained. Since our program began, a total of approximately 3,200 hours of lidar/radiometer data have been collected, resulting in a uniquely comprehensive, and climatologically-representative, high cloud dataset. In this report, we highlight our research accomplishments over the period of performance of this grant.

Sassen, Kenneth↗

Hyperspectral Remote Sensing of Atmosphere and Surface Properties

Atmospheric Infrared Sounder (AIRS), Infrared Atmospheric Sounding Interferometer (IASI), and Cross-track Infrared Sounder (CrIS) are all hyper-spectral satellite sensors with thousands of spectral channels. Top of atmospheric radiance spectra measured by these sensors contain high information content on atmospheric, cloud, and surface properties. Exploring high information content contained in these high spectral resolution spectra is a challenging task due to computation e ort involved in modeling thousands of spectral channels. Usually, only very small fractions (4{10 percent) of the available channels are included in physical retrieval systems or numerical weather forecast (NWP) satellite data assimilations. We will describe a method of simultaneously retrieving atmospheric temperature, moisture, cloud, and surface properties using all available spectral channels without sacrificing computational speed. The essence of the method is to convert channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Because the EOFs are orthogonal to each other, about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) developed at NASA Langley Research Center is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. There is no need to perform EOF transformations to convert super channels back to spectral space at each iteration step for a one-dimensional variational retrieval or a NWP data assimilation system. The PCRTM forward model is also capable of calculating radiative contributions due to multiple-layer clouds. The multiple scattering effects of the clouds are efficiently parameterized. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance matrices and a priori information as constraints. One advantage of this approach is that it uses all information content from the hyper-spectral data so that the retrieval is less sensitive to instrument noise and eliminates the need for selecting a sub-set of the channels.

Liu, Xu↗

Parameterization of bulk condensation in numerical cloud models

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.

Kogan, Yefim L.↗

A parameterization for the shortwave transmissivity of stratiform water clouds based on empirical data and radiative transfer theory

Surface measurements of solar flux and total integrated liquid-water content, radiosonde data, and infrared satellite images are analyzed in conjunction with radiative transfer calculations to derive an empirical parameterization for the shortwave transmissivity of continental stratiform water clouds. The data were collected near Denver, Colorado, over a period of six years. A multiple reflection radiative transfer model is employed to estimate stratus cloud transmissivity in terms of the measurable liquid-water path (LWP). A nonlinear fit of estimated transmissivities to the corresponding observations of LWP yields close agreement with a previous, more complicated parameterization. The derived expression for cloud transmissivity is used to predict mean daily surface fluxes for 61 days during which periods of stratiform clouds were observed over the Denver area. A comparison between predicted and measured fluxes shows agreement to within + or - 4 percent, with best agreement for clouds of moderate optical thickness. Potential sources of error are identified with sensitivity studies.

Derr, V. E.↗

The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post‐Cold‐Frontal Clouds over the ARM East North Atlantic Site

The correct representation of lowlevel midlatitude clouds found in the wake of cold fronts strongly relies on the representation of planetary boundary layer (PBL) and convection processes, which are typically parameterized separately in numerical models. Using the Weather Research and Forecasting Model (WRF), this study investigates how distinct pairs of PBL and convection parameterization schemes represent cloud fraction in the postcoldfrontal region. The simulations focus on the region of the DOEARM Eastern North Atlantic observation site in the Azores Islands in the wake of a cold front that passed on December 25, 2015. Different PBL and convection schemes are combined to create 12 distinct configurations. The main differences between the selected physical parameterizations are the strength of vertical mixing and the entrainment. The simulations produce a wide range of cloud fractions, where some configurations significantly underestimate while others clearly overestimate satellite and surfacebased estimates of cloud fraction. A skill score is used to quantitatively assess the performance of each configuration with respect to groundbased radar data. The key processes that are found to significantly impact the cloud fraction distribution are the strength of the PBL decoupling, the vertical wind shear, entrainment and detrainment rates in shallow convection and the occurrence of drizzle. This indicates that to successfully simulate postcoldfrontal clouds, modeled physics must balance strong internal vertical mixing and weak exchange with the free troposphere. For this case study, cloud fraction was more sensitive to the choice of convection scheme than PBL scheme.

moist convection interaction between parameterizat↗

Reflected fluxes for broken clouds over a Lambertian surface

Reflected fluxes are calculated for broken cloudiness (i.e., nonplane parallel) as a function of cloud cover, cloud optical depth, solar zenith angle and surface albedo. These calculations extend previous results for broken cloud reflected fluxes over a black surface. The present study demonstrates that not only radiances but also radiative fluxes over high albedo surfaces may be decreased by the presence of broken cloudiness. Conventional wisdom states that cloud radiances (brightnesses) are always greater than the background. While most cloud retrieval schemes are built around this assumption, it is incorrect for clouds over high albedo surfaces such as found in polar regions. However, the most startling and counterintuitive conclusion of this study is that nonabsorbing finite clouds over a highly reflecting surface will decrease the system albedo. As a result, surface absorption is increased, the result of multiple scattering between surface and cloud layer, controlled by cloud morphology and cloud optical thickness. A simple parameterization of the effects of cloud contamination upon retrieved albedo is given in terms of solar zenith angle, cloud optical depth, surface albedo, cloud cover, and plane-parallel cloud albedo. In this way, the effects of broken cloudiness are modeled in terms of easily computed plane-parallel values.

Welch, Ronald M.↗

The Influence of Soil Moisture and Wind on Rainfall Distribution and Intensity in Florida

Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of soil moisture will affect sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of soil moisture and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of soil moisture distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial soil moisture distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of soil moisture and wind to rainfall distribution and intensity is determined.

Baker, R. David↗

Soil Moisture, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida

Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as soil moisture distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of soil moisture and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of soil moisture influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature affects the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (soil moisture and coastline curvature) are required to fully account for observed rainfall amounts.

Baker, R. David↗

Lightning Scaling Laws Revisited

Scaling laws relating storm electrical generator power (and hence lightning flash rate) to charge transport velocity and storm geometry were originally posed by Vonnegut (1963). These laws were later simplified to yield simple parameterizations for lightning based upon cloud top height, with separate parameterizations derived over land and ocean. It is demonstrated that the most recent ocean parameterization: (1) yields predictions of storm updraft velocity which appear inconsistent with observation, and (2) is formally inconsistent with the theory from which it purports to derive. Revised formulations consistent with Vonnegut's original framework are presented. These demonstrate that Vonnegut's theory is, to first order, consistent with observation. The implications of assuming that flash rate is set by the electrical generator power, rather than the electrical generator current, are examined. The two approaches yield significantly different predictions about the dependence of charge transfer per flash on storm dimensions, which should be empirically testable. The two approaches also differ significantly in their explanation of regional variability in lightning observations.

Boccippio, D. J.↗

Aerosol-Ice Formation Closure Pilot Study (AEROICSTUDY) Field Campaign Report

The aerosol-ice formation closure pilot study (AEROICESTUDY) was a field campaign conducted at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility at the Southern Great Plains (SGP) observatory from October 7 to 28, 2019. The purpose of this campaign was to test a field observational approach for conducting an aerosol-ice formation closure study. In other words, the goal was to predict the number of ice nucleating particles (INPs) from the measurements of physical and chemical aerosol properties and compare those to measured INP number concentrations. This project was motivated by the fact that the aerosol community has widely conducted aerosol radiative closure, aerosol-cloud condensation nuclei (CCN), and CCN-droplet closure studies to test the physical models and parameterizations that cloud-resolving and climate models rely on to perform reliable simulations of the Earth system and energy budget. However, very few closure studies related to INPs have been conducted, and to our knowledge, none using robust, size-resolved, ambient aerosol composition measurements as model inputs.

aerosol-ice formation↗

Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY) Field Campaign Report

The aerosol-ice formation closure pilot study (AEROICESTUDY) was a field campaign conducted at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility at the Southern Great Plains (SGP) observatory from October 7 to 28, 2019. The purpose of this campaign was to test a field observational approach for conducting an aerosol-ice formation closure study. In other words, the goal was to predict the number of ice nucleating particles (INPs) from the measurements of physical and chemical aerosol properties and compare those to measured INP number concentrations. This project was motivated by the fact that the aerosol community has widely conducted aerosol radiative closure, aerosol-cloud condensation nuclei (CCN), and CCN-droplet closure studies to test the physical models and parameterizations that cloud-resolving and climate models rely on to perform reliable simulations of the Earth system and energy budget. However, very few closure studies related to INPs have been conducted, and to our knowledge, none using robust, size-resolved, ambient aerosol composition measurements as model inputs

AEROICESTUDY↗