Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors.
Hossein Dadashazar, David Painemal, Majid Alipanah, Michael Brunke, Seethala Chellappan, Andrea F Corral, Ewan Crosbie, Simon Kirschler, Hongyu Liu, Richard H Moore, Claire Robinson, Amy Jo Scarino, Michael Shook, Kenneth Sinclair, K Lee Thornhill, Christiane Voigt, Hailong Wang, Edward Winstead, Xubin Zeng, Luke Ziemba, Paquita Zuidema, Armin Sorooshian
Author Information
Hossein Dadashazar: Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA.
David Painemal: NASA Langley Research Center, Hampton, VA, USA.
Majid Alipanah: Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA.
Michael Brunke: Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA.
Seethala Chellappan: Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA.
Andrea F Corral: Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA.
Ewan Crosbie: NASA Langley Research Center, Hampton, VA, USA.
Simon Kirschler: Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany.
Hongyu Liu: National Institute of Aerospace, Hampton, VA, USA.
Richard H Moore: NASA Langley Research Center, Hampton, VA, USA.
Claire Robinson: NASA Langley Research Center, Hampton, VA, USA.
Amy Jo Scarino: NASA Langley Research Center, Hampton, VA, USA.
Michael Shook: NASA Langley Research Center, Hampton, VA, USA.
Kenneth Sinclair: NASA Goddard Institute for Space Studies, New York, NY, USA.
K Lee Thornhill: NASA Langley Research Center, Hampton, VA, USA.
Christiane Voigt: Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany.
Hailong Wang: Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Edward Winstead: NASA Langley Research Center, Hampton, VA, USA.
Xubin Zeng: Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA.
Luke Ziemba: NASA Langley Research Center, Hampton, VA, USA.
Paquita Zuidema: Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA.
Armin Sorooshian: Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA.
Cloud drop number concentrations ( ) 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 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- days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high- 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 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 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- relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of .
