CCN Closure Study for Amazonian Dry Season Biomass Burning Aerosol
Anders
Erik
Vestin, Div. of Nuclear Physics, Lund University, P.O. Box 118, SE-22100 Lund, Sweden, anders.vestin@nuclear.lu.se
Erik
Swietlicki, Div. of Nuclear Physics, Lund University, P.O. Box 118, SE-22100 Lund, Sweden, erik.swietlicki@nuclear.lu.se
Jenny
Rissler, Div. of Nuclear Physics, Lund University, P.O. Box 118, SE-22100 Lund, Sweden, jenny.rissler@pixe.lth.se
Jingchuan
Zhou, Div. of Nuclear Physics, Lund University, P.O. Box 118, SE-22100 Lund, Sweden, jczhou@hawaii.edu
Göran
Frank, Max Planck Institute for Chemistry, Biogeochemistry Department, P.O. Box 3060, D-55020, Mainz, Germany, gfrank@mpch-mainz.mpg.de
Meinrat
O.
Andreae, Max Planck Institute for Chemistry, Biogeochemistry Department, P.O. Box 3060, D-55020, Mainz, Germany, andreae@mpch-mainz.mpg.de
(Presenting)
A CCN closure study was performed during the LBA-SMOCC dry season experiment in Amazonia, September-November 2002 where the interactions between smoke from biomass burning, cloud microphysics, precipitation and climate were investigated. Measurements were performed with a DMPS that measures the dry particle size distribution and a H-TDMA measuring hygroscopic diameter growth of individual aerosol particles. A static thermal-gradient CCN counter was used to measure the CCN concentration. Size-resolved particle volume fraction of water-soluble material responsible for the activation into cloud droplets was estimated from H-TDMA measurements, and used in a modified Köhler theory to predict the CCN concentration as a function of the water vapour supersaturation. Our results show that during intensive biomass burning periods, the particles were generally less hygroscopic than at background conditions. The temporal variability of the measured CCN concentrations could be predicted from the DMPS and H-TDMA data. For the seven water vapour supersaturations covered by the CCN counter (0.23 – 1.12 %), the regression of predicted versus measured CCN concentrations had slopes between 0.70 (1.12%) and 0.95 (0.3%) with R2 between 0.94 – 0.97. The CCN spectra can be parameterized for selected time periods or air masses using a simple, but physically sound model. Similar validated parameterizations are available for wet season background conditions (CLAIRE-98 and CLAIRE-2001). This offers a possibility to incorporate a validated description of the CCN properties of the Amazonian biomass burning aerosol into cloud parcel models to study the impact of biomass burning on cloud structure and microphysics.