Dataset Information

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

ABSTRACT: During the Marine Aerosol Cloud and Wildfire Study (MACAWS) in June and July of 2018, aerosol composition and cloud condensation nuclei (CCN) properties were measured over the N.E. Pacific to characterize the influence of aerosol hygroscopicity on predictions of ambient CCN and stratocumulus cloud droplet number concentrations (CDNC). Three vertical regions were characterized, corresponding to the marine boundary layer (MBL), an above-cloud organic aerosol layer (AC-OAL), and the free troposphere (FT) above the AC-OAL. The aerosol hygroscopicity parameter (?) was calculated from CCN measurements (? CCN) and bulk aerosol mass spectrometer (AMS) measurements (? AMS). Within the MBL, measured hygroscopicities varied between values typical of both continental environments (~0.2) and remote marine locations (~0.7). For most flights, CCN closure was achieved within 20% in the MBL. For five of the seven flights, assuming a constant aerosol size distribution produced similar or better CCN closure than assuming a constant "marine" hygroscopicity (? = 0.72). An aerosol-cloud parcel model was used to characterize the sensitivity of predicted stratocumulus CDNC to aerosol hygroscopicity, size distribution properties, and updraft velocity. Average CDNC sensitivity to accumulation mode aerosol hygroscopicity is 39% as large as the sensitivity to the geometric median diameter in this environment. Simulations suggest CDNC sensitivity to hygroscopicity is largest in marine stratocumulus with low updraft velocities (<0.2 m s-1), where accumulation mode particles are most relevant to CDNC, and in marine stratocumulus or cumulus with large updraft velocities (>0.6 m s-1), where hygroscopic properties of the Aitken mode dominate hygroscopicity sensitivity.

SUBMITTER: Schulze BC

PROVIDER: S-EPMC7676499 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

Schulze B C BC Charan S M SM Kenseth C M CM Kong W W Bates K H KH Williams W W Metcalf A R AR Jonsson H H HH Woods R R Sorooshian A A Flagan R C RC Seinfeld J H JH

Earth and space science (Hoboken, N.J.) 20200603 7

During the Marine Aerosol Cloud and Wildfire Study (MACAWS) in June and July of 2018, aerosol composition and cloud condensation nuclei (CCN) properties were measured over the N.E. Pacific to characterize the influence of aerosol hygroscopicity on predictions of ambient CCN and stratocumulus cloud droplet number concentrations (CDNC). Three vertical regions were characterized, corresponding to the marine boundary layer (MBL), an above-cloud organic aerosol layer (AC-OAL), and the free tropospher ...[more]

PMID: 33225018

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Project description:Cloud drop number concentrations (N d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N d.

Dataset Information

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

Publications

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

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