scholarly journals The Influence of Entrainment and Mixing Assumption on Aerosol–Cloud Interactions in Marine Stratocumulus

2009 ◽  
Vol 66 (5) ◽  
pp. 1450-1464 ◽  
Author(s):  
Adrian A. Hill ◽  
Graham Feingold ◽  
Hongli Jiang

Abstract This study uses large-eddy simulation with bin microphysics to investigate the influence of entrainment and mixing on aerosol–cloud interactions in the context of idealized, nocturnal, nondrizzling marine stratocumulus (Sc). Of particular interest are (i) an evaporation–entrainment effect and a sedimentation–entrainment effect that result from increasing aerosol concentrations and (ii) the nature of mixing between clear and cloudy air, where homogeneous and extreme inhomogeneous mixing represent the bounding mixing types. Simulations are performed at low resolution (Δz = 20 m; Δx, y = 40 m) and high resolution (Δz = 10 m; Δx, y = 20 m). It is demonstrated that an increase in aerosol from clean conditions (100 cm−3) to polluted conditions (1000 cm−3) produces both an evaporation–entrainment and a sedimentation–entrainment effect, which couple to cause about a 10% decrease in liquid water path (LWP) when all warm microphysical processes are included. These dynamical effects are insensitive to both the resolutions tested and the mixing assumption. Regardless of resolution, assuming extreme inhomogeneous rather than homogeneous mixing results in a small reduction in cloud-averaged drop number concentration, a small increase in cloud drop effective radius, and ∼1% decrease in cloud optical depth. For the case presented, these small changes play a negligible role when compared to the impact of increasing aerosol and the associated entrainment effects. Finally, it is demonstrated that although increasing resolution causes an increase in LWP and number concentration, the relative sensitivity of cloud optical depth to changes in aerosol is unaffected by resolution.

2016 ◽  
Vol 16 (2) ◽  
pp. 933-952 ◽  
Author(s):  
D. Merk ◽  
H. Deneke ◽  
B. Pospichal ◽  
P. Seifert

Abstract. Cloud properties from both ground-based as well as from geostationary passive satellite observations have been used previously for diagnosing aerosol–cloud interactions. In this investigation, a 2-year data set together with four selected case studies are analyzed with the aim of evaluating the consistency and limitations of current ground-based and satellite-retrieved cloud property data sets. The typically applied adiabatic cloud profile is modified using a sub-adiabatic factor to account for entrainment within the cloud. Based on the adiabatic factor obtained from the combination of ground-based cloud radar, ceilometer and microwave radiometer, we demonstrate that neither the assumption of a completely adiabatic cloud nor the assumption of a constant sub-adiabatic factor is fulfilled (mean adiabatic factor 0.63 ± 0.22). As cloud adiabaticity is required to estimate the cloud droplet number concentration but is not available from passive satellite observations, an independent method to estimate the adiabatic factor, and thus the influence of mixing, would be highly desirable for global-scale analyses. Considering the radiative effect of a cloud described by the sub-adiabatic model, we focus on cloud optical depth and its sensitivities. Ground-based estimates are here compared vs. cloud optical depth retrieved from the Meteosat SEVIRI satellite instrument resulting in a bias of −4 and a root mean square difference of 16. While a synergistic approach based on the combination of ceilometer, cloud radar and microwave radiometer enables an estimate of the cloud droplet concentration, it is highly sensitive to radar calibration and to assumptions about the moments of the droplet size distribution. Similarly, satellite-based estimates of cloud droplet concentration are uncertain. We conclude that neither the ground-based nor satellite-based cloud retrievals applied here allow a robust estimate of cloud droplet concentration, which complicates its use for the study of aerosol–cloud interactions.


2019 ◽  
Vol 147 (5) ◽  
pp. 1491-1511 ◽  
Author(s):  
Timothy Glotfelty ◽  
Kiran Alapaty ◽  
Jian He ◽  
Patrick Hawbecker ◽  
Xiaoliang Song ◽  
...  

Abstract The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) is developed for studying aerosol effects on gridscale and subgrid-scale clouds using common aerosol activation and ice nucleation formulations and double-moment cloud microphysics in a scale-aware subgrid-scale parameterization scheme. Comparisons of both the standard WRF and WRF-ACI models’ results for a summer season against satellite and reanalysis estimates show that the WRF-ACI system improves the simulation of cloud liquid and ice water paths. Correlation coefficients for nearly all evaluated parameters are improved, while other variables show slight degradation. Results indicate a strong cloud lifetime effect from current climatological aerosols increasing domain average cloud liquid water path and reducing domain average precipitation as compared to a simulation with aerosols reduced by 90%. Increased cloud-top heights indicate a thermodynamic invigoration effect, but the impact of thermodynamic invigoration on precipitation is overwhelmed by the cloud lifetime effect. A combination of cloud lifetime and cloud albedo effects increases domain average shortwave cloud forcing by ~3.0 W m−2. Subgrid-scale clouds experience a stronger response to aerosol levels, while gridscale clouds are subject to thermodynamic feedbacks because of the design of the WRF modeling framework. The magnitude of aerosol indirect effects is shown to be sensitive to the choice of autoconversion parameterization used in both the gridscale and subgrid-scale cloud microphysics, but spatial patterns remain qualitatively similar. These results indicate that the WRF-ACI model provides the community with a computationally efficient tool for exploring aerosol–cloud interactions.


2012 ◽  
Vol 12 (2) ◽  
pp. 1031-1049 ◽  
Author(s):  
A. McComiskey ◽  
G. Feingold

Abstract. A wide range of estimates exists for the radiative forcing of the aerosol effect on cloud albedo. We argue that a component of this uncertainty derives from the use of a wide range of observational scales and platforms. Aerosol influences cloud properties at the microphysical scale, or the "process scale", but observations are most often made of bulk properties over a wide range of resolutions, or "analysis scales". We show that differences between process and analysis scales incur biases in quantification of the albedo effect through the impact that data aggregation and computational approach have on statistical properties of the aerosol or cloud variable, and their covariance. Measures made within this range of scales are erroneously treated as equivalent, leading to a large uncertainty in associated radiative forcing estimates. Issues associated with the coarsening of observational resolution particular to quantifying the albedo effect are discussed. Specifically, the omission of the constraint on cloud liquid water path and the separation in space of cloud and aerosol properties from passive, space-based remote sensors dampen the measured strength of the albedo effect. We argue that, because of this lack of constraints, many of these values are in fact more representative of the full range of aerosol-cloud interactions and their associated feedbacks. Based on our understanding of these biases we propose a new observationally-based and process-model-constrained, method for estimating aerosol-cloud interactions that can be used for radiative forcing estimates as well as a better characterization of the uncertainties associated with those estimates.


2020 ◽  
Vol 20 (6) ◽  
pp. 3609-3621
Author(s):  
Anna Possner ◽  
Ryan Eastman ◽  
Frida Bender ◽  
Franziska Glassmeier

Abstract. The liquid water path (LWP) adjustment due to aerosol–cloud interactions in marine stratocumulus remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP adjustments to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. We utilise the susceptibility framework to quantify the potential change in LWP adjustment with boundary layer (BL) depth in subtropical marine stratocumulus. We show that the LWP susceptibility, i.e. the relative change in LWP scaled by the relative change in cloud droplet number concentration, in marine BLs triples in magnitude from −0.1 to −0.31 as the BL deepens from 300 to 1200 m and deeper. We further find deep BLs to be underrepresented in pollution tracks, process modelling, and in situ studies of aerosol–cloud interactions in marine stratocumulus. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology may underestimate the true LWP adjustment within subtropical stratocumulus and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates in deep BLs remain poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they overestimate pollution track estimates.


2019 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  

Abstract. The evaluation of modeling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM with satellite observations using MOderate Resolution Imaging Spectrometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model to model and model to satellite comparisons. Cloud droplet number concentrations (CDNC) are derived identically from MODIS-COSP simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distribution of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases on the Northern Hemisphere. We computed the aerosol-cloud interactions as the sensitivity of dln(CDNC)/dln(AI) on a global scale. However, one year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies which are necessary steps to further improve the parametrization in climate models.


2011 ◽  
Vol 11 (5) ◽  
pp. 15497-15550 ◽  
Author(s):  
Y.-C. Chen ◽  
L. Xue ◽  
Z. J. Lebo ◽  
H. Wang ◽  
R. M. Rasmussen ◽  
...  

Abstract. Three-dimensional large-eddy simulations (LES) with detailed bin-resolved microphysics are performed to explore the diurnal variation of marine stratocumulus (MSc) clouds under clean and polluted conditions. The sensitivity of the aerosol-cloud-precipitation interactions to variation of sea surface temperature, free tropospheric humidity, large-scale divergence rate, and wind speed is assessed. The comprehensive set of simulations corroborates previous studies that (1) with moderate/heavy drizzle, an increase in aerosol leads to an increase in cloud thickness; and (2) with non/light drizzle, an increase in aerosol results in a thinner cloud, due to the pronounced effect on entrainment. It is shown that for higher SST, stronger large-scale divergence, drier free troposphere, or lower wind speed, the cloud thins and precipitation decreases. The sign and magnitude of the Twomey effect, droplet dispersion effect, cloud thickness effect, and overall cloud optical depth susceptibility to aerosol perturbations are evaluated by LES experiments and compared with analytical formulations. The Twomey effect emerges as dominant in total cloud susceptibility to aerosol perturbations. The dispersion effect, that of aerosol perturbations on the cloud droplet size spectrum, is positive (i.e., increase in aerosol leads to spectral narrowing) and accounts for 3 % to 10 % of the total cloud susceptibility at nighttime, with the largest influence in heavier drizzling clouds. The cloud thickness effect is negative (i.e., increase in aerosol leads to thinner cloud) for non/light drizzling cloud and positive for moderate/heavy drizzling clouds; the cloud thickness effect contributes 5 % to 22 % of the nighttime cloud susceptibility. The range of magnitude for each effect is more variable in the daytime owing to cloud thinning and decoupling. Overall, the cloud susceptibility is ~0.28 to 0.53 at night; an increase in aerosol concentration enhances cloud optical depth, especially with heavier precipitation and in a more pristine environment. The good agreement between LES experiments and analytical formulations suggests that the latter may be useful in evaluations of cloud susceptibility. The ratio of the magnitude of the cloud thickness effect to that of the Twomey effect depends on cloud base height and cloud thickness in unperturbed (clean) clouds.


2020 ◽  
Vol 20 (3) ◽  
pp. 1607-1626 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  

Abstract. The evaluation of modelling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models (ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM) with satellite observations using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model-to-model and model-to-satellite comparisons. Cloud droplet number concentrations (CDNCs) are derived identically from MODIS-COSP-simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distributions of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases in the Northern Hemisphere. We evaluate the aerosol–cloud interactions by computing the sensitivity parameter ACICDNC=dln⁡(CDNC)/dln⁡(AI) on a global scale. However, 1 year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies, which are necessary steps to further improve the parameterisation in climate models.


2011 ◽  
Vol 11 (18) ◽  
pp. 9749-9769 ◽  
Author(s):  
Y.-C. Chen ◽  
L. Xue ◽  
Z. J. Lebo ◽  
H. Wang ◽  
R. M. Rasmussen ◽  
...  

Abstract. Three-dimensional large-eddy simulations (LES) with detailed bin-resolved microphysics are performed to explore the diurnal variation of marine stratocumulus (MSc) clouds under clean and polluted conditions. The sensitivity of the aerosol-cloud-precipitation interactions to variation of sea surface temperature, free tropospheric humidity, large-scale divergence rate, and wind speed is assessed. The comprehensive set of simulations corroborates previous studies that (1) with moderate/heavy drizzle, an increase in aerosol leads to an increase in cloud thickness; and (2) with non/light drizzle, an increase in aerosol results in a thinner cloud, due to the pronounced effect on entrainment. It is shown that for higher SST, stronger large-scale divergence, drier free troposphere, or lower wind speed, the cloud thins and precipitation decreases. The sign and magnitude of the Twomey effect, droplet dispersion effect, cloud thickness effect, and cloud optical depth susceptibility to aerosol perturbations (i.e., change in cloud optical depth to change in aerosol number concentration) are evaluated by LES experiments and compared with analytical formulations. The Twomey effect emerges as dominant in total cloud optical depth susceptibility to aerosol perturbations. The dispersion effect, that of aerosol perturbations on the cloud droplet size spectrum, is positive (i.e., increase in aerosol leads to spectral narrowing) and accounts for 3% to 10% of the total cloud optical depth susceptibility at nighttime, with greater influence in heavier drizzling clouds. The cloud thickness effect is negative (i.e., increase in aerosol leads to thinner cloud) for non/light drizzling cloud and positive for a moderate/heavy drizzling clouds; the cloud thickness effect contributes 5% to 22% of the nighttime total cloud susceptibility. Overall, the total cloud optical depth susceptibility ranges from ~0.28 to 0.53 at night; an increase in aerosol concentration enhances cloud optical depth, especially with heavier precipitation and in a more pristine environment. During the daytime, the range of magnitude for each effect is more variable owing to cloud thinning and decoupling. The good agreement between LES experiments and analytical formulations suggests that the latter may be useful in evaluations of the total cloud susceptibility. The ratio of the magnitude of the cloud thickness effect to that of the Twomey effect depends on cloud base height and cloud thickness in unperturbed (clean) clouds.


2018 ◽  
Vol 11 (10) ◽  
pp. 5837-5864 ◽  
Author(s):  
Hiren Jethva ◽  
Omar Torres ◽  
Changwoo Ahn

Abstract. Aerosol–cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of adequate knowledge of the complex microphysical and radiative processes of the aerosol–cloud system. Situations when light-absorbing aerosols such as carbonaceous particles and windblown dust overlay low-level cloud decks are commonly found in several regions of the world. Contrary to the known cooling effects of these aerosols in cloud-free scenario over darker surfaces, an overlapping situation of the absorbing aerosols over the cloud can lead to a significant level of atmospheric absorption exerting a positive radiative forcing (warming) at the top of the atmosphere. We contribute to this topic by introducing a new global product of above-cloud aerosol optical depth (ACAOD) of absorbing aerosols retrieved from the near-UV observations made by the Ozone Monitoring Instrument (OMI) onboard NASA's Aura platform. Physically based on an unambiguous “color ratio” effect in the near-UV caused by the aerosol absorption above the cloud, the OMACA (OMI above-cloud aerosols) algorithm simultaneously retrieves the optical depths of aerosols and clouds under a prescribed state of the atmosphere. The OMACA algorithm shares many similarities with the two-channel cloud-free OMAERUV algorithm, including the use of AIRS carbon monoxide for aerosol type identification, CALIOP-based aerosol layer height dataset, and an OMI-based surface albedo database. We present the algorithm architecture, inversion procedure, retrieval quality flags, initial validation results, and results from a 12-year long OMI record (2005–2016) including global climatology of the frequency of occurrence, ACAOD, and aerosol-corrected cloud optical depth. A comparative analysis of the OMACA-retrieved ACAOD, collocated with equivalent accurate measurements from the HSRL-2 lidar for the ORACLES Phase I operation (August–September 2016), revealed a good agreement (R = 0.77, RMSE = 0.10). The long-term OMACA record reveals several important regions of the world, where the carbonaceous aerosols from the seasonal biomass burning and mineral dust originated over the continents are found to overlie low-level cloud decks with moderate (0.3 < ACAOD < 0.5, away from the sources) to higher levels of ACAOD (> 0.8 in the proximity to the sources), including the southeastern Atlantic Ocean, southern Indian Ocean, Southeast Asia, the tropical Atlantic Ocean off the coast of western Africa, and northern Arabian sea. No significant long-term trend in the frequency of occurrence of aerosols above the clouds and ACAOD is noticed when OMI observations that are free from the “row anomaly” throughout the operation are considered. If not accounted for, the effects of aerosol absorption above the clouds introduce low bias in the retrieval of cloud optical depth with a profound impact on increasing ACAOD and cloud brightness. The OMACA aerosol product from OMI presented in this paper offers a crucial missing piece of information from the aerosol loading above cloud that will help us to quantify the radiative effects of clouds when overlaid with aerosols and their resultant impact on cloud properties and climate.


2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.


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