Drivers of cloud droplet number variability in the summertime in the southeastern United States

Abstract. Here we analyze regional-scale data collected on board the NOAA WP-3D aircraft during the 2013 Southeast Nexus (SENEX) campaign to study the aerosol–cloud droplet link and quantify the sensitivity of droplet number to aerosol number, chemical composition, and vertical velocity. For this, the observed aerosol size distributions, chemical composition, and vertical-velocity distribution are introduced into a state-of-the-art cloud droplet parameterization to show that cloud maximum supersaturations in the region range from 0.02 % to 0.52 %, with an average of 0.14±0.05 %. Based on these low values of supersaturation, the majority of activated droplets correspond to particles with a dry diameter of 90 nm and above. An important finding is that the standard deviation of the vertical velocity (σw) exhibits considerable diurnal variability (ranging from 0.16 m s−1 during nighttime to over 1.2 m s−1 during day), and it tends to covary with total aerosol number (Na). This σw–Na covariance amplifies the predicted response in cloud droplet number (Nd) to Na increases by 3 to 5 times compared to expectations based on Na changes alone. This amplified response is important given that droplet formation is often velocity-limited and therefore should normally be insensitive to aerosol changes. We also find that Nd cannot exceed a characteristic concentration that depends solely on σw. Correct consideration of σw and its covariance with time and Na is important for fully understanding aerosol–cloud interactions and the magnitude of the aerosol indirect effect. Given that model assessments of aerosol–cloud–climate interactions do not routinely evaluate for overall turbulence or its covariance with other parameters, datasets and analyses such as the one presented here are of the highest priority to address unresolved sources of hydrometeor variability, bias, and the response of droplet number to aerosol perturbations.

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Drivers of cloud droplet number variability in the summertime Southeast United States

10.5194/acp-2020-225 ◽

2020 ◽

Author(s):

Aikaterini Bougiatioti ◽

Athanasios Nenes ◽

Jack J. Lin ◽

Charles A. Brock ◽

Joost de Gouw ◽

...

Keyword(s):

United States ◽

Chemical Composition ◽

Vertical Velocity ◽

Regional Scale ◽

Cloud Droplet ◽

Warming Trend ◽

Aerosol Formation ◽

Southeast United States ◽

Diurnal Variability ◽

Aerosol Cloud

Abstract. The Southeast United States has experienced a different climate warming trend compared to other places worldwide. Several hypotheses have been proposed to explain this trend, one being the interaction of anthropogenic and biogenic aerosol precursors that synergistically promote aerosol formation, elevate cloud droplet concentration and induce regional cooling. We examine these aerosol-cloud droplet links by analyzing regional scale data collected onboard the NOAA WP-3D aircraft during the 2013 Southeast Nexus (SENEX) campaign to quantify the sensitivity of droplet number to aerosol number, chemical composition and vertical velocity on a regional scale. The observed aerosol size distributions, chemical composition and vertical velocity distribution (Gaussian with standard deviation σw) are introduced into a state-of-the-art cloud droplet parameterization to show that cloud maximum supersaturations in the region are low, ranging from 0.02 to 0.52 % with an average of 0.14 ± 0.05 %. Based on these low values of supersaturation, the majority of activated droplets correspond to particles of diameter 90 nm and above. Droplet number shows little sensitivity to total aerosol owing to their strong competition for water vapor. Given, however, that σw exhibits considerable diurnal variability (ranging from 0.16 m/s during nighttime to over 1.2 m/s during day), its covariance with total aerosol number (Na) during the same period amplifies predicted response in cloud droplet number (Nd) by 3 to 5 times. Therefore, correct consideration of vertical velocity and its covariance with time and aerosol amount is important for fully understanding aerosol-cloud interactions and the magnitude of the aerosol indirect effect. Datasets and analysis such as the one presented here can provide the required constraints for addressing this important problem.

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Cloud droplet variability in the summertime in the southeast United States: day vs. night

10.5194/egusphere-egu21-16245 ◽

2021 ◽

Author(s):

Aikaterini Bougiatioti ◽

Athanasios Nenes ◽

Jack Lin ◽

Charles Brock ◽

Joost de Gouw ◽

...

Keyword(s):

Chemical Composition ◽

Vertical Velocity ◽

Cloud Droplet ◽

Limited Effect ◽

Southeast United States ◽

Diurnal Variability ◽

Upper Limit ◽

Velocity Changes ◽

Do So

During the 2013 Southeast Nexus (SENEX) campaign, in-situ observational data were collected on board the NOAA WP-3D aircraft to study the aerosol-cloud droplet link and examine the sensitivity of the cloud droplet number to aerosol physicochemical parameters. In order to do so, observed aerosol number size distributions, chemical composition and vertical-velocity distributions were introduced into a state-of-the-art cloud droplet parameterization from which cloud droplet number and cloud maximum supersaturations were derived. We find that the standard deviation of the vertical velocity (&#963;w) exhibits significant diurnal variability ranging from 0.16 m s-1 during nighttime to over 1.2 m s-1 during day. Total aerosol number (Na) covaries with &#963;w , with lower values observed during nighttime. The covariance between &#963;w and Na enhances the apparent response of Nd to changes in Na levels by a factor of 5. For the same &#8220;cleaner&#8221; environments where Na values are limited and not impacted by local sources, the relative response of Nd to &#963;w is almost twice as great during night, compared to the day (24% during day vs. 42% during night). On the other hand, in environment with enhanced concentrations, especially of accumulation-mode particles, the majority of droplet number variability is attributed to changes in total aerosol number rather than changes in &#963;w. Chemical composition is found to on-average have a limited effect on Nd variability (4%). Finally, we identify an upper limit to the number of droplets that can form in clouds which depends only on &#963;w independently from total aerosol number. Doubling &#963;w from 0.2 to 0.3 m s-1increases this limiting droplet number by 52%.When Nd values approach this upper limit the observed droplet variability is driven by &#963;w and, subsequently, by vertical-velocity changes only. Therefore only by using this -&#963;w relationship in regions where velocity-limited conditions are expected, &#963;w can be estimated from retrievals of droplet number and vice versa.

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The effect of local sources on particle size and chemical composition and their role in aerosol-cloud interactions

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-32133-2013 ◽

2013 ◽

Vol 13 (12) ◽

pp. 32133-32173 ◽

Cited By ~ 2

Author(s):

H. Portin ◽

A. Leskinen ◽

L. Hao ◽

A. Kortelainen ◽

P. Miettinen ◽

...

Keyword(s):

Chemical Composition ◽

Cloud Droplet ◽

Special Focus ◽

Size Distributions ◽

Air Masses ◽

Accumulation Mode ◽

Aerosol Cloud ◽

Local Sources ◽

Clean Air ◽

Aerosol Cloud Interactions

Abstract. The effects of local pollutant sources and particle chemical composition on aerosol–cloud interactions were investigated by measuring cloud interstitial and total aerosol size distributions, particle chemical composition and hygroscopic growth factors and cloud droplet size distributions on an observation tower, with a special focus on comparing clean air masses with those affected by local sources. The polluted air masses contained more particles than the clean air masses in all size classes, excluding the accumulation mode. This was caused by cloud processing, which was also observed for the polluted air but to a lesser extent. Some, mostly minor, differences in the particle chemical composition between the air masses were observed. The average size and number concentration of activating particles were quite similar for both air masses, producing average droplet populations with only minor distinctions. As a case study, a long cloud event was analyzed in detail regarding emissions from local sources, including a paper mill and a heating plant. Clear differences in the total and accumulation mode particle concentrations, particle hygroscopicity and chemical composition during the cloud event were observed. Particularly, larger particles, higher hygroscopicities and elevated amounts of inorganic constituents, especially SO4, were linked with the pollutant plumes. In the air masses affected by traffic and domestic wood combustion, a bimodal particle hygroscopicity distribution was observed, indicating externally mixed aerosol. The variable conditions during the event had a clear impact on cloud droplet formation.

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Implementation of aerosol–cloud interactions in the regional atmosphere–aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

Geoscientific Model Development ◽

10.5194/gmd-10-2231-2017 ◽

2017 ◽

Vol 10 (6) ◽

pp. 2231-2246 ◽

Cited By ~ 5

Author(s):

Sudhakar Dipu ◽

Johannes Quaas ◽

Ralf Wolke ◽

Jens Stoll ◽

Andreas Mühlbauer ◽

...

Keyword(s):

Satellite Data ◽

Transport Model ◽

Cloud Condensation Nuclei ◽

Cloud Droplet ◽

Atmospheric Model ◽

Horizontal Resolution ◽

Small Scale ◽

Aerosol Model ◽

Aerosol Cloud ◽

Aerosol Cloud Interactions

Abstract. The regional atmospheric model Consortium for Small-scale Modeling (COSMO) coupled to the Multi-Scale Chemistry Aerosol Transport model (MUSCAT) is extended in this work to represent aerosol–cloud interactions. Previously, only one-way interactions (scavenging of aerosol and in-cloud chemistry) and aerosol–radiation interactions were included in this model. The new version allows for a microphysical aerosol effect on clouds. For this, we use the optional two-moment cloud microphysical scheme in COSMO and the online-computed aerosol information for cloud condensation nuclei concentrations (Cccn), replacing the constant Cccn profile. In the radiation scheme, we have implemented a droplet-size-dependent cloud optical depth, allowing now for aerosol–cloud–radiation interactions. To evaluate the models with satellite data, the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) has been implemented. A case study has been carried out to understand the effects of the modifications, where the modified modeling system is applied over the European domain with a horizontal resolution of 0.25°  ×  0.25°. To reduce the complexity in aerosol–cloud interactions, only warm-phase clouds are considered. We found that the online-coupled aerosol introduces significant changes for some cloud microphysical properties. The cloud effective radius shows an increase of 9.5 %, and the cloud droplet number concentration is reduced by 21.5 %.

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The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-15413-2016 ◽

2016 ◽

Vol 16 (23) ◽

pp. 15413-15424 ◽

Cited By ~ 39

Author(s):

Takuro Michibata ◽

Kentaroh Suzuki ◽

Yousuke Sato ◽

Toshihiko Takemura

Keyword(s):

General Circulation ◽

Climate Models ◽

Circulation Model ◽

Cloud Droplet ◽

Systematic Difference ◽

Liquid Water Path ◽

Light Rain ◽

Aerosol Cloud ◽

Nonlinear Complexity ◽

Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

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Untangling causality in midlatitude aerosol-cloud adjustments

10.5194/acp-2019-665 ◽

2019 ◽

Cited By ~ 1

Author(s):

Daniel T. McCoy ◽

Paul Field ◽

Hamish Gordon ◽

Gregory S. Elsaesser ◽

Daniel P. Grosvenor

Keyword(s):

Radiative Forcing ◽

Sensible Heat Flux ◽

Cloud Droplet ◽

Causal Link ◽

Cloud Microphysics ◽

Liquid Water Path ◽

Aerosol Cloud ◽

Causal Pathways ◽

Model Adjustment ◽

Aerosol Cloud Interactions

Abstract. Aerosol-cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol-cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path averaged across cloudy and clear regions (LWP, here, characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol-cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol, and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP, and MODIS are compared to simulations in the MetOffice Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence, and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol-cloud adjustments. By removing variability associated with meteorology and scavenging we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25–30 % overestimate by the UM GA7.1 in LWP change and a 30–35% overestimate in associated radiative forcing.

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Investigation of aerosol–cloud interactions under different absorptive aerosol regimes using Atmospheric Radiation Measurement (ARM) southern Great Plains (SGP) ground-based measurements

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-3483-2020 ◽

2020 ◽

Vol 20 (6) ◽

pp. 3483-3501 ◽

Cited By ~ 1

Author(s):

Xiaojian Zheng ◽

Baike Xi ◽

Xiquan Dong ◽

Timothy Logan ◽

Yuan Wang ◽

...

Keyword(s):

Great Plains ◽

Cloud Droplet ◽

Atmospheric Radiation ◽

Strong Light ◽

Southern Great Plains ◽

Aerosol Cloud ◽

Atmospheric Radiation Measurement ◽

The Mean ◽

Aerosol Cloud Interactions ◽

Absorbing Aerosols

Abstract. The aerosol indirect effect on cloud microphysical and radiative properties is one of the largest uncertainties in climate simulations. In order to investigate the aerosol–cloud interactions, a total of 16 low-level stratus cloud cases under daytime coupled boundary-layer conditions are selected over the southern Great Plains (SGP) region of the United States. The physicochemical properties of aerosols and their impacts on cloud microphysical properties are examined using data collected from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the SGP site. The aerosol–cloud interaction index (ACIr) is used to quantify the aerosol impacts with respect to cloud-droplet effective radius. The mean value of ACIr calculated from all selected samples is 0.145±0.05 and ranges from 0.09 to 0.24 at a range of cloud liquid water paths (LWPs; LWP=20–300 g m−2). The magnitude of ACIr decreases with an increasing LWP, which suggests a diminished cloud microphysical response to aerosol loading, presumably due to enhanced condensational growth processes and enlarged particle sizes. The impact of aerosols with different light-absorbing abilities on the sensitivity of cloud microphysical responses is also investigated. In the presence of weak light-absorbing aerosols, the low-level clouds feature a higher number concentration of cloud condensation nuclei (NCCN) and smaller effective radii (re), while the opposite is true for strong light-absorbing aerosols. Furthermore, the mean activation ratio of aerosols to CCN (NCCN∕Na) for weakly (strongly) absorbing aerosols is 0.54 (0.45), owing to the aerosol microphysical effects, particularly the different aerosol compositions inferred by their absorptive properties. In terms of the sensitivity of cloud-droplet number concentration (Nd) to NCCN, the fraction of CCN that converted to cloud droplets (Nd∕NCCN) for the weakly (strongly) absorptive regime is 0.69 (0.54). The measured ACIr values in the weakly absorptive regime are relatively higher, indicating that clouds have greater microphysical responses to aerosols, owing to the favorable thermodynamic condition. The reduced ACIr values in the strongly absorptive regime are due to the cloud-layer heating effect induced by strong light-absorbing aerosols. Consequently, we expect larger shortwave radiative cooling effects from clouds in the weakly absorptive regime than those in the strongly absorptive regime.

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Investigation of the adiabatic assumption for estimating cloud micro- and macrophysical properties from satellite and ground observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-933-2016 ◽

2016 ◽

Vol 16 (2) ◽

pp. 933-952 ◽

Cited By ~ 24

Author(s):

D. Merk ◽

H. Deneke ◽

B. Pospichal ◽

P. Seifert

Keyword(s):

Optical Depth ◽

Microwave Radiometer ◽

Cloud Droplet ◽

Satellite Observations ◽

Data Set ◽

Cloud Optical Depth ◽

Cloud Radar ◽

Aerosol Cloud ◽

Droplet Concentration ◽

Aerosol Cloud Interactions

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.

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The contribution of the strength and structure of extratropical cyclones to observed cloud–aerosol relationships

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-10689-2013 ◽

2013 ◽

Vol 13 (21) ◽

pp. 10689-10701 ◽

Cited By ~ 7

Author(s):

B. S. Grandey ◽

P. Stier ◽

R. G. Grainger ◽

T. M. Wagner

Keyword(s):

Large Scale ◽

Relative Vorticity ◽

Extratropical Cyclones ◽

Small Component ◽

Aerosol Cloud ◽

Climate Interactions ◽

Local Meteorology ◽

Moderate Resolution Imaging Spectroradiometer ◽

Regression Slopes ◽

Aerosol Cloud Interactions

Abstract. Meteorological conditions may drive relationships between aerosol and cloud-related properties. It is important to account for the meteorological contribution to observed cloud–aerosol relationships in order to improve understanding of aerosol–cloud–climate interactions. A new method of investigating the contribution of meteorological covariation to observed cloud–aerosol relationships is introduced. Other studies have investigated the contribution of local meteorology to cloud–aerosol relationships. In this paper, a complimentary large-scale view is presented. Extratropical cyclones have been previously shown to affect satellite-retrieved aerosol optical depth (τ), due to enhanced emission of sea salt and sea surface brightness artefacts in regions of higher wind speed. Extratropical cyclones have also been shown to affect cloud-related properties such as cloud fraction (fc) and cloud top temperature (Ttop). Therefore, it seems plausible to hypothesise that extratropical cyclones may drive relationships between cloud-related properties and τ. In this paper, this hypothesis is investigated for extratropical cyclones, henceforth referred to as storms, over the Atlantic Ocean. MODerate resolution Imaging Spectroradiometer (MODIS) retrieved τ, fc and Ttop data are analysed using a storm-centric coordinate system centred on extratropical cyclones which have been tracked using European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis 850 hPa relative vorticity data. The tracked relative vorticity (ω) is used as a measure of storm strength, while position in the storm-centric domain is used to account for storm structure. Relationships between the cloud-related properties and τ are measured by calculating regression slopes and correlations. The fc–τ relationships are positive, while the Ttop–τ relationships are negative. By shuffling the pairing of the cloud and τ data at each location in the storm-centric domain and within narrow ω bins, the contribution of storm strength and storm structure to the observed relationships can be investigated. It is found that storm strength and storm structure can explain only a small component of the relationships observed in the MODIS data. The primary causes for observed cloud–aerosol relationships are likely to be other factors such as retrieval errors, local meteorology or aerosol–cloud interactions.

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A global satellite view of aerosol cloud interactions

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-4-6823-2004 ◽

2004 ◽

Vol 4 (5) ◽

pp. 6823-6836 ◽

Cited By ~ 3

Author(s):

C. Luo

Keyword(s):

North Africa ◽

North Atlantic ◽

Radiative Forcing ◽

General Circulation ◽

Large Scale ◽

Regional Scale ◽

Cloud Amount ◽

General Circulation Models ◽

Aerosol Cloud ◽

Aerosol Cloud Interactions

Abstract. Long-term and large-scale correlations between Advanced Very High-Resolution Radiometer (AVHRR) aerosol optical depth and International Satellite Cloud Climatology Project (ISCCP) monthly cloud amount data show significant regional scale relationships between cloud amount and aerosols, consistent with aerosol-cloud interactions. Positive correlations between aerosols and cloud amount are associated with North American and Asian aerosols in the North Atlantic and Pacific storm tracks, and mineral aerosols in the tropical North Atlantic. Negative correlations are seen near biomass burning regions of North Africa and Indonesia, as well as south of the main mineral aerosol source of North Africa. These results suggest that there are relationships between aerosols and clouds in the observations that can be used by general circulation models to verify the correct forcing mechanisms for both direct and indirect radiative forcing by clouds.

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