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

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.

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

2020 ◽  
Vol 20 (20) ◽  
pp. 12163-12176 ◽  
Author(s):  
Aikaterini Bougiatioti ◽  
Athanasios Nenes ◽  
Jack J. Lin ◽  
Charles A. Brock ◽  
Joost A. de Gouw ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Vertical Velocity ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Diurnal Variability ◽  
Aerosol Cloud ◽  
Climate Interactions ◽  
Characteristic Concentration ◽  
Aerosol Cloud Interactions ◽  
The One

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.

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

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

<p>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 (σ<sub>w</sub>) exhibits significant diurnal variability ranging from 0.16 m s<sup>-1</sup> during nighttime to over 1.2 m s<sup>-1</sup> during day. Total aerosol number (N<sub>a</sub>) covaries with σ<sub>w</sub> , with lower values observed during nighttime. The covariance between σ<sub>w</sub> and N<sub>a</sub> enhances the apparent response of N<sub>d</sub> to changes in N<sub>a</sub> levels by a factor of 5. For the same “cleaner” environments where N<sub>a</sub> values are limited and not impacted by local sources, the relative response of N<sub>d</sub> to σ<sub>w</sub> 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 σ<sub>w</sub>. Chemical composition is found to on-average have a limited effect on N<sub>d</sub> variability (4%). Finally, we identify an upper limit to the number of droplets that can form in clouds which depends only on σ<sub>w</sub> independently from total aerosol number. Doubling σ<sub>w</sub> from 0.2 to 0.3 m s<sup>-1</sup>increases this limiting droplet number by 52%.When N<sub>d</sub> values approach this upper limit the observed droplet variability is driven by σ<sub>w </sub>and, subsequently, by vertical-velocity changes only. Therefore only by using this -σ<sub>w</sub> relationship in regions where velocity-limited conditions are expected, σ<sub>w</sub> can be estimated from retrievals of droplet number and vice versa.</p>

scholarly journals The challenge of simulating the sensitivity of the Amazonian clouds microstructure to cloud condensation nuclei number concentrations

2019 ◽  
Author(s):  
Pascal Polonik ◽  
Christoph Knote ◽  
Tobias Zinner ◽  
Florian Ewald ◽  
Tobias Kölling ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Cloud Base ◽  
Condensation Nuclei ◽  
Aerosol Cloud ◽  
Microphysical Properties

Abstract. The realistic representation of cloud-aerosol interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon area has been one of the motivations for several field observations, including the airborne Aerosol, Cloud, Precipitation, and Radiation Interactions and DynamIcs of CONvective cloud systems – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA) campaign based in Manaus, Brazil in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysical properties (droplet number concentration and effective radius). We found agreement between modeled and observed median cloud droplet number concentrations (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of two was found, which means a systematic underestimation of modeled CDNC as compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations and cloud droplet effective radii (reff) was also underestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN per cm3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Regional background aerosol concentrations were sufficiently high such that the additional CCN emitted from local fires did not cause a notable change in modelled cloud microphysical properties. In addition, we evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedo effect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm−3.

scholarly journals Varied Diagnosis of the Observed Surface Temperature Trends in the Southeast United States

2013 ◽  
Vol 26 (4) ◽  
pp. 1467-1472 ◽  
Author(s):  
V. Misra ◽  
J.-P. Michael
Keyword(s):  
United States ◽  
Winter Season ◽  
Warming Trend ◽  
Southeast United States ◽  
Temperature Trends ◽  
Four Seasons ◽  
Time Period ◽  
Cooling Trend ◽  
Relationship Of ◽  
The Relationship

Abstract This paper diagnoses the temperature trends in maximum (Tmax) and minimum temperatures (Tmin) over a selection of 65 stations spread over the southeast United States (SEUS) from three observed datasets. They are the Cooperative Observer network program (COOP), the COOP data corrected for documented shifts in time of observation (COOP1), and the COOP data additionally corrected for documented changes in instrumentation (COOP2). These 65 stations have been isolated for having the three observed datasets for the same time period from 1948 to 2009. The authors’ comparisons suggest that COOP2 displays stronger warming (cooling) trends in Tmax (Tmin) compared with COOP1 in all four seasons. This is consistent with the expectation from the bias correction applied for the instrument change. In comparison, the differences between COOP and COOP2 are relatively larger. In the spring, summer, and fall seasons, the median Tmax trend is warming in COOP2 while it is cooling in COOP. In the winter season, the median trends of Tmax in the two datasets are positive, but their magnitudes are substantially different. Similarly, in the winter, summer, and fall seasons, the warming trend in Tmin in COOP is contrary to the cooling trend in COOP2. In the spring season, the median trend in Tmin is comparable between the two datasets. COOP2 shows the relationship of trends in Tmin, with the extent of urbanization in these 65 stations, to be statistically significant and to be consistent with expectations from theory in contrast to the COOP data.

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

2013 ◽  
Vol 13 (12) ◽  
pp. 32133-32173 ◽  
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.

scholarly journals Exploring aerosol cloud interaction using VOCALS-REx aircraft measurements

2018 ◽  
Author(s):  
Hailing Jia ◽  
Xiaoyan Ma ◽  
Yangang Liu
Keyword(s):  
Vertical Velocity ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Relative Dispersion ◽  
Aircraft Measurements ◽  
Cloud Droplets ◽  
Aerosol Cloud ◽  
Microphysical Properties ◽  
Entrainment Zone ◽  
The Difference

Abstract. In situ aircraft measurements during the VAMOS Ocean–Cloud–Atmosphere–Land Study-Regional Experiment (VOCALS-REx) field campaign are employed to study the interaction between aerosol and stratocumulus over the southeast Pacific Ocean, as well as entrainment process near the top of stratocumulus and its possible impacts on aerosol–cloud interaction. Our analysis suggest that the increase of liquid water content (LWC) is mainly contributed by cloud droplet number concentration (Nd) instead of effective radius of cloud droplets in the polluted case, in which more droplets form with smaller size, while the opposite is true in the clean case. By looking into the influences of dynamical conditions and aerosol microphysical properties on the cloud droplet formation, it is confirmed that cloud droplets are more easily to form under the conditions with large vertical velocity and aerosol size. An increase in aerosol concentration tends to increase both Nd and relative dispersion (ϵ), while an increase in vertical velocity (w) often increases Nd but decreases ϵ. After constraining the differences of cloud dynamics, positive correlation between ϵ and Nd become stronger, implying that perturbations of w could weaken the influence of aerosol on ϵ, and hence may result in an underestimation of aerosol dispersion effect. The difference of cloud microphysical properties between entrainment and non-entrainment zones confirms that the entrainment-mixing mechanism is predominantly extreme inhomogeneous in the stratocumulus that capped by a sharp inversion, namely the entrainment reduces Nd and LWC by 28.9 % and 24.8 % on average, respectively, while the size of droplets is relatively unaffected. In entrainment zone, smaller aerosols and drier air entrained from the top induce less cloud droplet with respect to total in-cloud particles (0.56 ± 0.22) than the case in non-entrainment zone (0.73 ± .0.13) by inhibiting aerosol activation and promoting cloud droplets evaporation.

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