Giant Sea-Salt Aerosols and Warm Rain Formation in Marine Stratocumulus

2008 ◽  
Vol 65 (12) ◽  
pp. 3678-3694 ◽  
Author(s):  
Jørgen B. Jensen ◽  
Sunhee Lee
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Cloud Model ◽  
Sea Salt ◽  
Droplet Growth ◽  
Anthropogenic Factors ◽  
Marine Stratocumulus ◽  
Sea Salt Aerosols ◽  
Warm Rain ◽  
Rain Formation

Abstract The concentrations and sizes of smaller aerosols (radius smaller than 0.5 μm) in the marine atmosphere vary owing to natural and anthropogenic factors. The concentrations and sizes of giant and ultragiant aerosols vary primarily due to wind-speed-dependent wave breaking. In climate models the formation of warm rain from marine stratocumulus clouds is usually parameterized based on the drops that form on the smaller aerosols. The present process study, using a stochastic Monte Carlo cloud model, shows that the variability of giant sea-salt aerosols and the variability of smaller aerosol cloud condensation nuclei are equally important in determining precipitation flux in marine stratocumulus. This strongly suggests that the effects of giant sea-salt aerosols should be included in the parameterization of warm rain formation in climate and other large-scale models. The above results are based on highly detailed calculations of droplet growth in an idealized marine stratocumulus cloud; the authors believe that other marine stratus cloud conditions may change the calculated rain rates but that the conclusions regarding the relative importance of small and giant aerosols are robust.

Warm Cloud Evolution, Precipitation, and Their Weak Linkage in HadGEM3: New Process-Level Diagnostics using A-Train Observations

2021 ◽  
Author(s):  
Hanii Takahashi ◽  
Alejandro Bodas-Salcedo ◽  
Graeme Stephens
Keyword(s):  
Large Scale ◽  
Cloud Droplet ◽  
Formation Processes ◽  
Evaluation Tool ◽  
Liquid Water Path ◽  
Microphysics Scheme ◽  
Warm Rain ◽  
Weak Linkage ◽  
The Impact ◽  
Rain Formation

AbstractThe latest configuration of the Hadley Centre Global Environmental Model version 3 (HadGEM3) contains significant changes in the formulation of warm rain processes and aerosols. We evaluate the impacts of these changes in the simulation of warm rain formation processes using A-Train observations. We introduce a new model evaluation tool, quartile-based Contoured Frequency by Optical Depth Diagrams (CFODDs), in order to fill in some blind spots that conventional CFODDs have. Results indicate that HadGEM3 has weak linkage between the size of particle radius and warm rain formation processes, and switching to the new warm rain microphysics scheme causes more difference in warm rain formation processes than switching to the new aerosol scheme through reducing overly produced drizzle mode in HadGEM3. Finally, we run an experiment in which we perturb the second aerosol indirect effect (AIE) to study the rainfall-aerosol interaction in HadGEM3. Since the large changes in the cloud droplet number concentration (CDNC) appear in the AIE experiment, a large impact in warm rain diagnostics is expected. However, regions with large fractional changes in CDNC show a muted change in precipitation, arguably because large-scale constraints act to reduce the impact of such a big change in CDNC. The adjustment in cloud liquid water path to the AIE perturbation produces a large negative shortwave forcing in the midlatitudes.

Virtual Field Campaigns on Deep Tropical Convection in Climate Models

2009 ◽  
Vol 22 (2) ◽  
pp. 244-257 ◽  
Author(s):  
Brian Mapes ◽  
Julio Bacmeister ◽  
Marat Khairoutdinov ◽  
Cecile Hannay ◽  
Ming Zhao
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Cloud Model ◽  
Convective Heating ◽  
Cloud Forcing ◽  
Community Atmosphere Model ◽  
Virtual Field ◽  
Atmosphere Model ◽  
Rain Events ◽  
Tropospheric Heating

Abstract High-resolution time–height data over warm tropical oceans are examined, from three global atmosphere models [GFDL’s Atmosphere Model 2 (AM2), NCAR’s Community Atmosphere Model, version 3 (CAM3), and a NASA Global Modeling and Assimilation Office (GMAO) model], field campaign observations, and observation-driven cloud model outputs. The character of rain events is shown in data samples and summarized in lagged regressions versus surface rain rate. The CAM3 humidity and cloud exhibit little vertical coherence among three distinct layers, and its rain events have a short characteristic time, reflecting the convection scheme’s penetrative nature and its closure’s concentrated sensitivity to a thin boundary layer source level. In contrast, AM2 rain variations have much longer time scales as convection scheme plumes whose entrainment gives them tops below 500 hPa interact with humidity variations in that layer. Plumes detraining at model levels above 500 hPa are restricted by cloud work function thresholds, and upper-tropospheric humidity and cloud layers fed by these are detached from the lower levels and are somewhat sporadic. With these discrete entrainment rates and instability thresholds, AM2 also produces some synthetic-looking noise (sharp features in height and time) on top of its slow rain variations. A distinctive feature of the NASA model is a separate anvil scheme, distinct from the main large-scale cloud scheme, fed by relaxed Arakawa–Schubert (RAS) plume ensemble convection (a different implementation than in AM2). Its variability is rich and vertically coherent, and involves a very strong vertical dipole component to its tropospheric heating variations, of both signs (limited-depth convective heating and top-heavy heating in strong deep events with significant nonconvective rain). Grid-scale saturation events occur in all three models, often without nonconvective surface rain, causing relatively rare episodes of large negative top-of-atmosphere cloud forcing. Overall, cloud forcing regressions show a mild net positive forcing by rain-correlated clouds in CAM3 and mild net cooling in the other models, as the residual of large canceling shortwave and longwave contributions.

Giant aerosols increase precipitation in marine cumulus and stratocumulus clouds

2020 ◽  
Author(s):  
Piotr Dziekan ◽  
Jorgen Jensen ◽  
Wojciech Grabowski ◽  
Hanna Pawłowska
Keyword(s):  
Cloud Model ◽  
Sea Salt ◽  
Cloud Seeding ◽  
Cloud Droplets ◽  
Sea Salt Aerosols ◽  
Stratocumulus Clouds ◽  
Bin Microphysics ◽  
The University ◽  
The Impact ◽  
Precipitation Formation

<p>Sea-salt aerosols with radii exceeding 1 μm have been observed over the oceans. Cloud droplets formed on these giant aerosols can quickly grow to drizzle sizes through condensation of water vapor. Therefore giant aerosols, although not numerous, have been speculated to increase the amount of precipitation produced in clouds. Testing this hypothesis in LES simulations has been difficult, because Eulerian microphysics models are not well suited to model growth of droplets on giant aerosols. On the contrary, Lagrangian microphysics models, which are an emerging alternative to the Eulerian bin microphysics models, can model giant aerosols in a straightforward manner.</p><p>LES simulations performed using the University of Warsaw Lagrangian Cloud Model (UWLCM) will be presented. In UWLCM, the Lagrangian super-droplet microphysics model is used. We will assess how giant aerosols affect precipitation formation in marine cumulus (setup based on the RICO campaign) and stratocumulus clouds (setup based on the research flight 2 of the DYCOMS campaign). It will be discussed how the impact of giant aerosols changes with the concentrations of giant and regular aerosols. The results are of importance also for cloud seeding experiments, in which giant sea-salt aerosols can be released into a cloud.</p>

scholarly journals Evaluate autoconversion and accretion enhancement factors in GCM warm-rain parameterizations using ground-based measurements at the Azores

2018 ◽  
Author(s):  
Peng Wu ◽  
Baike Xi ◽  
Xiquan Dong ◽  
Zhibo Zhang
Keyword(s):  
Climate Models ◽  
Spatial Scales ◽  
Precipitation Intensity ◽  
Climate Modelling ◽  
Warm Rain ◽  
Enhancement Factors ◽  
Rain Formation ◽  
Precipitating Clouds ◽  
Light Precipitation ◽  
Precipitation Events

Abstract. A great challenge in climate modelling is how to parametrize sub-grid cloud processes, such as autoconversion and accretion in warm rain formation. In this study, we use ground-based observations and retrievals over the Azores to investigate the so-called enhancement factors, Eauto and Eaccr, which are often used in climate models to account for the influences of sub-grid variances of cloud and precipitation water on the autoconversion and accretion processes. Eauto and Eaccr are computed at a variety of tempo-spatial scales corresponding to different model resolutions. The calculated Eauto increase from 1.79 (0.5-hr/36 km) to 3.15 (3.5-hr/126 km), and the calculated Eaccr increases from 1.25 (0.5-hr/36 km) to 1.6 (5-hr/180 km). Comparing the prescribed enhancement factors to the values from observations shows that GCMs are using a much higher Eauto (3.2) and lower Eaccr (1.07). This helps to explain why most of the GCMs produce too frequent precipitation events but with too light precipitation intensity. The ratios of rain to cloud liquid water at Eaccr = 1.07 and Eaccr = 2.0 are 0.048 and 0.119, respectively, further proving that the prescribed value of Eaccr = 1.07 used in GCMs is too small to simulate correct precipitation intensity. Both Eauto and Eaccr increase when the boundary layer becomes less stable, and the values are larger in precipitating clouds (CLWP > 75 gm−2) than those in nonprecipiting clouds (CLWP 

scholarly journals CCN activation and cloud processing in sectional aerosol models with low size resolution

2005 ◽  
Vol 5 (9) ◽  
pp. 2561-2570 ◽  
Author(s):  
H. Korhonen ◽  
V.-M. Kerminen ◽  
K. E. J. Lehtinen ◽  
M. Kulmala
Keyword(s):  
Size Distribution ◽  
Large Scale ◽  
Reference Model ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Anthropogenic Sources ◽  
Aerosol Size Distribution ◽  
Droplet Growth ◽  
Cloud Droplets ◽  
Cloud Processing

Abstract. We investigate the influence of low size resolution, typical to sectional aerosol models in large scale applications, on cloud droplet activation and cloud processing of aerosol particles. A simplified cloud model with five approaches to determine the fraction of activated particles is compared with a detailed reference model under different atmospheric conditions. In general, activation approaches which assume a distribution profile within the critical model size sections predict the cloud droplet concentration most accurately under clean and moderately polluted conditions. In such cases, the deviation from the reference simulations is below 15% except for very low updraft velocities. In highly polluted cases, the concentration of cloud droplets is significantly overestimated due to the inability of the simplified model to account for the kinetic limitations of the droplet growth. Of the profiles examined, taking into account the local shape of the particle size distribution is the most accurate although in most cases the shape of the profile has little relevance. While the low resolution cloud model cannot reproduce the details of the out-of-the-cloud aerosol size distribution, it captures well the amount of sulphate produced in aqueous-phase reactions as well as the distribution of the sulphate between the cloud droplets. Overall, the simplified cloud model with low size resolution performs well for clean and moderately polluted regions that cover most of the Earth's surface and is therefore suitable for large scale models. It can, however, show uncertainties in areas with strong pollution from anthropogenic sources.

scholarly journals Creating Truth Data to Quantify the Accuracy of Cloud Forecasts from Numerical Weather Prediction and Climate Models

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 177 ◽  
Author(s):  
Keith Hutchison ◽  
Barbara Iisager
Keyword(s):  
Satellite Imagery ◽  
Numerical Weather Prediction ◽  
Cloud Cover ◽  
Large Scale ◽  
Climate Models ◽  
Cloud Model ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Spectral Bands ◽  
Cloud Forecast

Clouds are critical in mechanisms that impact climate sensitivity studies, air quality and solar energy forecasts, and a host of aerodrome flight and safety operations. However, cloud forecast accuracies are seldom described in performance statistics provided with most numerical weather prediction (NWP) and climate models. A possible explanation for this apparent omission involves the difficulty in developing cloud ground truth databases for the verification of large-scale numerical simulations. Therefore, the process of developing highly accurate cloud cover fraction truth data from manually generated cloud/no-cloud analyses of multispectral satellite imagery is the focus of this article. The procedures exploit the phenomenology to maximize cloud signatures in a variety of remotely sensed satellite spectral bands in order to create accurate binary cloud/no-cloud analyses. These manual analyses become cloud cover fraction truth after being mapped to the grids of the target datasets. The process is demonstrated by examining all clouds in a NAM dataset along with a 24 h WRF cloud forecast field generated from them. Quantitative comparisons with the cloud truth data for the case study show that clouds in the NAM data are under-specified while the WRF model greatly over-predicts them. It is concluded that highly accurate cloud cover truth data are valuable for assessing cloud model input and output datasets and their creation requires the collection of satellite imagery in a minimum set of spectral bands. It is advocated that these remote sensing requirements be considered for inclusion into the designs of future environmental satellite systems.

scholarly journals CCN activation and cloud processing in simplified sectional aerosol models with low size resolution

2005 ◽  
Vol 5 (4) ◽  
pp. 4871-4892
Author(s):  
H. Korhonen ◽  
V.-M. Kerminen ◽  
K. E. J. Lehtinen ◽  
M. Kulmala
Keyword(s):  
Size Distribution ◽  
Large Scale ◽  
Reference Model ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Aerosol Size Distribution ◽  
Droplet Growth ◽  
Distribution Profile ◽  
Cloud Droplets ◽  
Cloud Processing

Abstract. We investigate the influence of low size resolution, typical to sectional aerosol models in large scale applications, on cloud droplet activation and cloud processing of aerosol particles. A simplified cloud scheme with five approaches to determine the fraction of activated particles is compared with a detailed reference model under different atmospheric conditions. In general, activation approaches which assume a distribution profile within the critical model size sections predict the cloud droplet concentration most accurately under clean and moderately polluted conditions. In such cases, the deviation from the reference simulations is below 15% except for very low updraft velocities. In highly polluted cases, the concentration of cloud droplets is significantly overestimated due to the inability of the simplified scheme to account for the kinetic limitations of the droplet growth. Of the profiles examined, taking into account the local shape of the particle size distribution is the most accurate although in most cases the shape of the profile has little relevance. While the low resolution cloud model cannot reproduce the details of the out-of-the-cloud aerosol size distribution, it captures well the amount of sulphate produced in aqueous-phase reactions as well as the distribution of the sulphate between the cloud droplets. Overall, the simplified cloud scheme with low size resolution performs well for clean and moderately polluted regions that cover most of the Earth's surface and is therefore suitable for large scale models.

scholarly journals Study of the Aerosol Indirect Effect by Large-Eddy Simulation of Marine Stratocumulus

2005 ◽  
Vol 62 (11) ◽  
pp. 3909-3932 ◽  
Author(s):  
Miao-Ling Lu ◽  
John H. Seinfeld
Keyword(s):  
Indirect Effect ◽  
Large Scale ◽  
Sea Salt ◽  
Relative Reduction ◽  
Cloud Droplets ◽  
Marine Stratocumulus ◽  
Aerosol Indirect Effect ◽  
Sea Salt Aerosol ◽  
Large Eddy ◽  
The Impact

Abstract A total of 98 three-dimensional large-eddy simulations (LESs) of marine stratocumulus clouds covering both nighttime and daytime conditions were performed to explore the response of cloud optical depth (τ) to various aerosol number concentrations (Na = 50–2500 cm−3) and the covarying meteorological conditions (large-scale divergence rate and SST). The idealized First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) and the Atlantic Stratocumulus Transition Experiment (ASTEX) Lagrangian 1 sounding profiles were used to represent the lightly and heavily drizzling cases, respectively. The first and second aerosol indirect effects are identified. Through statistical analysis, τ is found be to both positively correlated with Na and cloud liquid water path (LWP) with a higher correlation associated with LWP, which is predominantly regulated by large-scale subsidence and SST. Clouds with high LWP occur under low SST or weak large-scale subsidence. Introduction of a small amount of giant sea salt aerosol into the simulation lowers the number of cloud droplets activated, results in larger cloud droplets, and initiates precipitation for nondrizzling polluted clouds or precedes the precipitation process for drizzling clouds. However, giant sea salt aerosol is found to have a negligible effect on τ for lightly precipitating cases, while resulting in a relative reduction of τ of 3%–77% (increasing with Na, for Na = 1000–2500 cm−3) for heavily precipitating cases, suggesting that the impact of giant sea salt is only important for moist and potentially convective clouds. Finally, a regression analysis of the simulations shows that the second indirect effect is more evident in clear than polluted cases. The second indirect effect is found to enhance (reduce) the overall aerosol indirect effect for heavily (lightly) drizzling clouds; that is, τ is larger (smaller) for the same relative change in Na than considering the Twomey (first indirect) effect alone. The aerosol indirect effect (on τ) is lessened in the daytime afternoon conditions and is dominated by the Twomey effect; however, the effect in the early morning is close but slightly smaller than that in the nocturnal run. Diurnal variations of the aerosol indirect effect should be considered to accurately assess its magnitude.

The dependence of the breakup of marine stratocumulus on autoconversion parameterizations

2021 ◽  
Author(s):  
Zhoukun Liu ◽  
Minghuai Wang ◽  
Daniel Rosenfeld ◽  
Yannian Zhu
Keyword(s):  
Climate Models ◽  
Global Radiation ◽  
Transition Process ◽  
Radiation Budget ◽  
Marine Stratocumulus ◽  
Cloud Properties ◽  
Warm Rain ◽  
Precipitation Characteristics ◽  
Subtropical Oceans ◽  
Aerosol Cloud Interactions

<div> <div> <p>The marine stratocumulus (MSC) covers extensive regions of the eastern subtropical oceans, and it is an important contributor to the global radiation budget. Accompanied with precipitation, the regime of MSC often transform from closed cells (nearly overcast) to open cells (with cloud fraction ≤ 65%), which results in substantial decrease of cloud radiative effect (CRE). Given the fact that current parameterizations of warm rain formation process differ a lot from each other in climate models and the discrepancy of the precipitation characteristics between observation is usually large, observational constraints on the aerosol-cloud interactions in the transition process is particularly needed at current stage. In this study, the parameterization of autoconversion rate by Khairoutdinov and Kogan (2000) (KK2000 hereafter) embedded in a regional model, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is evaluated with the observed cloud and precipitation by satellites in the breakup transition process over the northeast Atlantic. The sensitivity tests show that the cloud properties precipitation characteristics, and CRE during the breakup process depends a lot on the parameters in KK2000, and satellite observations offer efficient constraints on the conventional autoconversion parameterizations.</p> </div> <div> </div> </div><div> <p> </p> </div>

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