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NASA NTRS2012

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↗

NASA NTRS2005

The Impact of Surface Albedo on the Retrievals of Low-Level Stratus Cloud Properties: An Updated Parameterization

An updated version of Dong et al. (1998, hereafter D98) parameterization is developed from a total of 40 hours of data with a broad range of surface albedos (0.1-0.8) during the 2000-2002 winter seasons at the DOE ARM SGP site. The updated parameterization includes the impact of surface albedo on the retrievals of stratus cloud microphysical and radiative properties, and has a significant improvement over D98 when surface albedo is high. Comparing the retrievals, the cloud-droplet effective radii (r(sub e)) calculated from the updated parameterization have a higher correlation coefficient (0.733) and lower Root-Mean-Square (RMS) error (1.74 m or 17.4%) than those (0.602, 4.0 m or 40%) from the D98. The cloud albedos also have a much higher correlation coefficient (0.983) and lower RMS (3%) than those 0.465, 26%) from the D98. The upper limit of surface albedo is 0.3 in applying the D98.

Dong, Xiquan↗

NASA NTRS1988

Theory on the uncertainty in cloud microphysical processes and climate

The interactive role of clouds and precipitation processes in a climate model is investigated. The basic model structure and parameterizations for condensation, evaporation, and precipitation are outlined. Results simulated from the cloud-climate model are discussed. The potential link between microphysical cloud processes and climate is theorized. The need to develop a climatology of the mean particle radius for clouds at the global scale, in order to understand the role of clouds in climate is stressed.

Liou, Kuo-Nan↗

NASA NTRS1988

Shortwave radiative parameterization of large atmospheric aerosols - Dust and water clouds

A parameterization of the single scattering properties of an aerosol for a dust layer in the solar spectral region is presented. The parameterization scheme accounts for the microphysical changes of an aerosol layer and is applied to dust and water clouds. A scaling parameter is presented which describes, simply and effectively, the optical properties of an aerosol layer with a large effective size parameter.

Ackerman, Steven A.↗

NASA NTRS1994

Case study of a low-reflectivity pulsating microburst: Numerical simulation of the Denver, 8 July 1989, storm

On 8 July 1989, a very strong microburst was detected by the Low-Level Windshear Alert system (LLWAS), within the approach corridor just north of Denver Stapleton Airport. The microburst was encountered by a Boeing 737-200 in a 'go-around' configuration which was reported to have lost considerable air speed and altitude during penetration. Data from LLWAS revealed a pulsating microburst with an estimated peak velocity change of 48 m/s. Wilson et al. reported that the microburst was accompanied by no apparent visible clues such as rain or virga, although blowing dust was present. Weather service hourly reports indicated virga in all quadrants near the time of the event. A National Center for Atmospheric Research (NCAR) research Doppler radar was operating; but according to Wilson et al., meaningful velocity could not be measured within the microburst due to low radar-reflectivity factor and poor siting for windshear detection at Stapleton. This paper presents results from the three-dimensional numerical simulation of this event, using the Terminal Area Simulation System (TASS) model. The TASS model is a three-dimensional nonhydrostatic cloud model that includes parameterizations for both liquid and ice phase microphysics, and has been used in investigations of both wet and dry microburst case studies. The focus of this paper is the pulsating characteristic and the very-low radar reflectivity of this event. Most of the surface outflow contained no precipitation. Such an event may be difficult to detect by radar.

Proctor, Fred H.↗

NASA NTRSDate not supplied

Boundary-Layer Cloud Modeling Challenges on the North Slope of Alaska

The accurate modeling and prediction of cloud base heights is critical for energy balance calculations and aviation operations, alike. Low-level (i.e., boundary-layer) Arctic clouds can be difficult to model, making prediction of formation and dissipation challenging. Primarily mixed-phase, these clouds typically contain low quantities of supercooled liquid water and often slowly precipitate relatively small amounts of moderately and heavily rimed snow particles. While this appears to be the predominant cloudy state on the North Slope of Alaska (NSA), the delicate balance of microphysical, dynamical, radiative, surface coupling, and advective processes can rapidly shift to heavy snow (with various degrees of riming) or to a complete dissipation of the cloud layer without any precipitation, depending on the dominant processes. Here we strive to disentangle these various processes. First, we compare the predictive performances of four different numerical weather models in forecasting the presence and base-heights of low-level clouds: the High-Resolution Rapid Refresh - Alaska (HRRR-AK) model, the Polar Weather Research and Forecasting (Polar WRF) model, the Unified Model (UM), and the European Centre for Medium-range Weather Forecasting (ECMWF) model. Initial results comparing model output at two U.S. Department of Energy Atmospheric Radiation Measurement (AMT) NSA sites, during the fall season in 2019 and 2022, show that the UM slightly outperforms the HRRR-AK in terms of accurately forecasting the presence of a low-level cloud layer (89% of the time). All models have a significant bias of 300 to 800 meters in forecasting cloud base height (lower than is observed); however, the UM and ECMWF models have the lowest biases. Finally, a case study for a particularly challenging April 2017 thin-cloud event is presented, wherein we compare the performance of four different bulk microphysical parameterization schemes using a higher-resolution large eddy simulation (LES) model, the WRF-LES. Initial results show that the Thompson scheme was the only one able to reproduce and sustain a substantial supercooled liquid layer, but it was unable to reproduce the transition from a deep, liquid-rich cloud to a thin layer with moderately and heavily rimed precipitation. This is the first step in linking simulated LES-scale riming processes with those parameterized at a coarser mesoscale model scale. This has important implications for forecasting low-level clouds in an operational environment, given the efficiency of the riming process.

cloud base heights↗

NASA NTRS2008

Optical-Microphysical Cirrus Model

A model is presented that permits the simulation of the optical properties of cirrus clouds as measured with depolarization Raman lidars. It comprises a one-dimensional cirrus model with explicit microphysics and an optical module that transforms the microphysical model output to cloud and particle optical properties. The optical model takes into account scattering by randomly oriented or horizontally aligned planar and columnar monocrystals and polycrystals. Key cloud properties such as the fraction of plate-like particles and the number of basic crystals per polycrystal are parameterized in terms of the ambient temperature, the nucleation temperature, or the mass of the particles. The optical-microphysical model is used to simulate the lidar measurement of a synoptically forced cirrostratus in a first case study. It turns out that a cirrus cloud consisting of only monocrystals in random orientation is too simple a model scenario to explain the observations. However, good agreement between simulation and observation is reached when the formation of polycrystals or the horizontal alignment of monocrystals is permitted. Moreover, the model results show that plate fraction and morphological complexity are best parameterized in terms of particle mass, or ambient temperature which indicates that the ambient conditions affect cirrus optical properties more than those during particle formation. Furthermore, the modeled profiles of particle shape and size are in excellent agreement with in situ and laboratory studies, i.e., (partly oriented) polycrystalline particles with mainly planar basic crystals in the cloud bottom layer, and monocrystals above, with the fraction of columns increasing and the shape and size of the particles changing from large thin plates and long columns to small, more isometric crystals from cloud center to top. The findings of this case study corroborate the microphysical interpretation of cirrus measurements with lidar as suggested previously.

Reichardt, J.↗

NASA NTRS2023

Electrification Within Wintertime Stratiform Regions Sampled During the 2020/2022 NASA IMPACTS Field Campaign

Two nor'easter events—sampled during the NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign—were examined to characterize the microphysics in relation to the underlying electrification processes within wintertime stratiform regions. A theoretical model was developed to determine whether accretion or diffusion growth regimes were preferential during periods of greatest electrification. Model simulation with electrification parameterization was used to provide supplemental context to the physical processes of in-cloud microphysics and electrification. The strongest electric fields (i.e., ∼80 V m −1 at 20 km) during the 2020 NASA IMPACTS deployment was associated with large non-rimed ice crystals colliding with each other. During the 29–30 January 2022 science flight, the NASA P-3 microphysical probe data demonstrated that non-inductive charging was possible off the coastline of Cape Cod, Massachusetts. Later in the science flight, when the NASA P-3 and ER-2 were coordinating with each other, measured electric fields consistently were less than 8 V m −1 and electrification was subdued owing to reduced concentrations of graupel and large ice hydrometeors. Altogether, the in-situ observations provide evidence for the non-riming collisional charging mechanism and demonstrates that graupel and supercooled liquid water may not be necessary for weak electrification within wintertime stratiform regions. Model output from simulation of both events suggested that the main synoptic snowbands were associated with elevated hydrometeor snow charge density and electric fields.

snowfall↗

NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, E. W., Jr.↗

NASA NTRS1990

Cloud optical parameters as derived from the multispectral cloud radiometer

Simultaneous measurements of the liquid water content and particle size have assumed an important role in cloud physics as they help elucidate the mechanism of cloud particle formation and the mechanism of air mass-mixing in stratus clouds. Such measurements can reveal the modification of cloud air masses by anthropogenic aerosol particles (Coakley et al. 1987, Durkee 1989). Studies of the climatic impact of these modification processes on cloud microphysics seems to be urgent for understanding mechanisms of climate change. General Circulation Model (GCM) simulations can be improved by introducing a parameterization of cloud optical properties in terms of integrated liquid water content (liquid water path) and particle size (Slingo 1989). Motivated by the above mentioned circumstances, remote sensing techniques were developed for simultaneously retrieving the cloud optical thickness and effective particle radius, from which the liquid water path can be inferred. Statistical features of the cloud optical thickness (or liquid water path) and effective particle size for marine stratocumulus clouds are presented. These results were obtained during 4 days (7, 10, 13, and 16 July 1987) of observations with the Multispectral Cloud Radiometer (ER-2) and the Thematic Mapper (LANDSAT-5) during the First ISCCP Regional Experiment (FIRE).

Nakajima, Teruyuki↗

NASA NTRS2006

Cloud Radiative Forcing at the ARM Climate Research Facility: Technique, Validation, and Comparison to Satellite-derived Diagnostic Quantities - Part 1

It has been hypothesized that continuous ground-based remote sensing measurements from active and passive remote sensors combined with regular soundings of the atmospheric thermodynamic structure can be combined to describe the effects of clouds on the clear sky radiation fluxes. We critically test that hypothesis in this paper and a companion paper (Part II). Using data collected at the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site sponsored by the U.S. Department of Energy, we explore an analysis methodology that results in the characterization of the physical state of the atmospheric profile at time resolutions of five minutes and vertical resolutions of 90 m. The description includes thermodynamics and water vapor profile information derived by merging radiosonde soundings with ground-based data, and continues through specification of the cloud layer occurrence and microphysical and radiative properties derived from retrieval algorithms and parameterizations. The description of the atmospheric physical state includes a calculation of the infrared and clear and cloudy sky solar flux profiles. Validation of the methodology is provided by comparing the calculated fluxes with top of atmosphere (TOA) and surface flux measurements and by comparing the total column optical depths to independently derived estimates. We find over a 1-year period of comparison in overcast uniform skies, that the calculations are strongly correlated to measurements with biases in the flux quantities at the surface and TOA of less than 10% and median fractional errors ranging from 20% to as low as 2%. In the optical depth comparison for uniform overcast skies during the year 2000 where the optical depth varies over 3 orders of magnitude we find a mean positive bias of 46% with a median bias of less than 10% and a 0.89 correlation coefficient. The slope of the linear regression line for the optical depth comparison is 0.86 with a normal deviation of 20% about this line. In addition to a case study where we examine the cloud radiative effects at the TOA, surface and atmosphere by a middle latitude synoptic-scale cyclone, we examine the cloud top pressure and optical depth retrievals of ISCCP and LBTM over a period of 1 year. Using overcast period from the year 2000, we find that the satellite algorithms tend to bias cloud tops into the middle troposphere and underestimate optical depth in high optical depth events (greater than 100) by as much as a factor of 2.

Mace, Gerald G.↗

NASA NTRS2001

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

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.

Menon, Surabi↗

NASA NTRS2001

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

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.

Menon, Surabi↗

NASA NTRS1991

Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection

The performance of several ice parameterizations has been evaluated through a numerical cloud model. Ice effects using different schemes are contrasted with each other and with an ice-free control by incorporating them into the cloud model and by applying them to simulations of tropical squall systems. The latter are simulated in 2D so that a large domain can be used to incorporate a complete anvil. Nonsquall-type convective lines are simulated in 3D owing to their smaller horizontal scale. It is concluded that inclusion of ice microphysics in the cloud model enhanced the agreement of the simulated convection with some features of observed convection, including the proportion of surface rainfall in the anvil region and the intensity and structure of the radar brightband near the melting level in the anvil. In the experiments with bulk microphysics, three ice categories produced much better results than two ice categories, which in turn was better than no ice. For the tropical squall-type and nonsquall-type systems the optimal mix was ice, snow, and graupel.

Mccumber, Michael↗

NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗

NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). Multiple models/reanalyses use SGS supersaturated total water (relative to GS saturation) as a threshold for partitioning available water for condensation, and indeed we find significant correlation between GS cloud water and SGS supersaturation. However, we also find that the assumption of a static threshold of 100% saturation to be unrealistic. Empirical calculations from the ARISE data show a large sensitivity of this threshold to GS relative humidity, and so a microphysical parameterization allowing the threshold to vary according to GS thermodynamic properties may result in more realistic GS cloud water values. Finally, to determine how sensitive the ARISE-derived results are to that particular campaign, we include additional data from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) conducted in 1998. The inclusion of the second dataset will help with demonstrating the robustness of the results and their utility in improving the representation of Arctic clouds in models and reanalyses.

J Brant Dodson↗

NASA NTRSDate not supplied

Evaluating Subgrid-Scale Properties of Low Clouds over the Beaufort Sea in Arctic System Reanalysis using ARISE Airborne In Situ Observations

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. To better understand the magnitude and possible causes of this problem, we analyze the disagreements between the Arctic System Reanalysis version 2 (ASR) and data taken during the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign conducted over the Beaufort Sea. Previous analysis of grid scale-averaged meteorological variables revealed a lack of cloud water produced in ASR, related to warm/dry biases, a failure to produce sufficient cloud water in conditions that are observed to be favorable for large cloud water values, and sampling issues with the ARISE flight paths. However, ARISE collected meteorological observations at one second intervals, offering spatial data resolution comparable to the subgrid scale of ASR. Subgrid scale properties and processes must be parameterized in conventional atmospheric models and reanalyses such as ASR, and often rely on assumed distributions of meteorological variables about the grid box mean state. To enable an examination of the realism of ASR’s subgrid scale properties, we use high resolution data from ARISE determine the “subgrid scale” distributions of cloud water and thermodynamic variables in the real atmosphere. Preliminary results show that the subgrid scale distribution of thermodynamic variables about the grid scale mean resembles the triangular distribution assumed in many bulk microphysical parameterization schemes, but also with tails resembling Gaussian distributions. The main goal is to understand the partitioning of the total available atmospheric water into water vapor and cloud water. Models typically covert some percentage of total water in a grid box to cloud water based on the estimated amount of supersaturation from the assumed vapor distribution. The ARISE measurements can reveal the relationship between subgrid scale supersaturation and the partition between cloud water and water vapor.

Jason Brant Dodson↗

NASA NTRS2012

Climate Impacts of Ice Nucleation

Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2).

Gettelman, Andrew↗