NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Collections About News Help Login
Back to Results
Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet FormationA total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.
Document ID
20190028655
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
doi:10.5194/acp-19-8591-2019
Authors
Fanourgakis, George S. (Crete Univ. Heraklion, Greece)
Kanakidou, Maria (Crete Univ. Heraklion, Greece)
Nenes, Athanasios (Ecole Polytechnique Federale de Lausanne Versoix, Switzerland)
Bauer, Susanne E. (NASA Goddard Inst. for Space Studies New York, NY, United States)
Bergman, Tommi (Royal Netherlands Meteorological Institute De Bilt, Netherlands)
Carslaw, Ken S. (University of Leeds Leeds, United Kingdom)
Grini, Alf
Hamilton, Douglas S. (Cornell Univ. Ithaca, NY, United States)
Johnson, Jill S. (University of Leeds Leeds, United Kingdom)
Karydis, Vlassis A. (Max-Planck-Institut für Chemie Mainz, Germany)
Kirkevag, Alf (Meteorologisk institutt Oslo, Norway)
Kodros, John K. (Colorado State Univ. Fort Collins, CO, United States)
Lohmann, Ulrike (Institute for Atmospheric and Climate Science Zurich, Switzerland)
Luo, Gan (State Univ. of New York Albany, NY, United States)
Makkonen, Risto (Finnish Meteorological Institute Helsinki, Finland)
Matsui, Hitoshi (Nagoya University Nagoya, Japan)
Neubauer, David (Institute for Atmospheric and Climate Science Zurich, Switzerland)
Pierce, Jeffrey R. (Colorado State Univ. Fort Collins, CO, United States)
Schmale, Julia (Paul Scherrer Institut Villigen, Switzerland)
Stier, Philip (University of Oxford Oxford, England, United Kingdom)
Tsigaridis, Kostas (Columbia Univ. New York, NY, United States)
van Noije, Twan (Royal Netherlands Meteorological Institute De Bilt, Netherlands)
Wang, Hailong (Pacific Northwest National Lab. Richland, WA, United States)
Watson-Parris, Duncan (University of Oxford Oxford, England, United Kingdom)
Westervelt, Daniel M. (Columbia Univ. New York, NY, United States)
Yang, Yang (Pacific Northwest National Lab. Richland, WA, United States)
Yoshioka, Masaru (University of Leeds Leeds, United Kingdom)
Daskalakis, Nikos (Universität Bremen Bremen, Germany)
Decesari, Stefano (Institute of Atmospheric Sciences and Climate (CNR-ISAC) Bologna, Italy)
Gysel-Beer, Martin (Paul Scherrer Institut Villigen, Switzerland)
Kalivitis, Nikos (Crete Univ. Heraklion, Greece)
Liu, Xiaohong (Wyoming Univ. Laramie, WY, United States)
Mahowald, Natalie M. (Cornell Univ. Ithaca, NY, United States)
Myriokefalitakis, Stelios (National Observatory of Athens Greece)
Schrodner, Roland (Lund University Lund, Sweden)
Sfakianaki, Maria (Crete Univ. Heraklion, Greece)
Tsimpidi, Alexandra P. (Max-Planck-Institut für Chemie Mainz, Germany)
Wu, Mingxuan (Wyoming Univ. Laramie, WY, United States)
Yu, Fangqun (State Univ. of New York Albany, NY, United States)
Date Acquired
August 1, 2019
Publication Date
July 8, 2019
Publication Information
Publication: Atmospheric Chemistry and Physics
Publisher: European Geosciences Union
Volume: 19
Issue: 13
ISSN: 1680-7316
e-ISSN: 1680-7324
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN70776
Funding Number(s)
CONTRACT_GRANT: 80NSSC17M0057
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Professional Review
Keywords
cloud droplets
cloud condensation
Aerosols

Related Records

There are no records associated with this record.
No Preview Available