scholarly journals Corrigendum to "The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei" published in Atmos. Chem. Phys., 13, 8879–8914, 2013

2013 ◽  
Vol 13 (18) ◽  
pp. 9375-9377 ◽  
Author(s):  
L. A. Lee ◽  
K. J. Pringle ◽  
C. L. Reddington ◽  
G. W. Mann ◽  
P. Stier ◽  
...  

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 786
Author(s):  
Mihalis Lazaridis

Bacteria activation and cloud condensation nuclei (CCN) formation have been studied in the atmosphere using the classical theory of heterogeneous nucleation. Simulations were performed for the binary system of sulfuric acid/water using laboratory-determined contact angles. Realistic model simulations were performed at different atmospheric heights for a set of 140 different bacteria. Model simulations showed that bacteria activation is a potentially favorable process in the atmosphere which may be enhanced at lower temperatures. CCN formation from bacteria nuclei is dependent on ambient atmospheric conditions (temperature, relative humidity), bacteria size, and sulfuric acid concentration. Furthermore, a critical parameter for the determination of bacteria activation is the value of the intermolecular potential between the bacteria’s surface and the critical cluster formed at their surface. In the classical nucleation theory, this is parameterized with the contact angle between substrate and critical cluster. Therefore, the dataset of laboratory values for the contact angle of water on different bacteria substrates needs to be enriched for realistic simulations of bacteria activation in the atmosphere.


2013 ◽  
Vol 13 (17) ◽  
pp. 8879-8914 ◽  
Author(s):  
L. A. Lee ◽  
K. J. Pringle ◽  
C. L. Reddington ◽  
G. W. Mann ◽  
P. Stier ◽  
...  

Abstract. Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN). Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.


2013 ◽  
Vol 13 (3) ◽  
pp. 6295-6378 ◽  
Author(s):  
L. A. Lee ◽  
K. J. Pringle ◽  
C. L. Reddington ◽  
G. W. Mann ◽  
P. Stier ◽  
...  

Abstract. The global distribution of cloud condensation nuclei (CCN) is the fundamental quantity that determines how changes in aerosols affect climate through changes in cloud drop concentrations, cloud albedo and precipitation. Aerosol-cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day CCN concentrations. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each monthly-mean model grid cell from an ensemble of 168 one-year model simulations covering the uncertainty space of the 28 parameters. The standard deviation around the mean CCN varies globally between about ±30% of the mean over some marine regions to ±40–100% over most land areas and high latitudes. The results imply that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol-cloud effects on climate. Variance decomposition enables the importance of the parameters for CCN uncertainty to be quantified and ranked from local to global scales. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulphate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulphur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulphate formation during cloud-processing. Most of the 28 parameters are important for CCN uncertainty somewhere on the globe. The results lead to several recommendations for research that would result in improved modelling of cloud-active aerosol on a global scale.


2008 ◽  
Vol 42 (22) ◽  
pp. 5728-5730 ◽  
Author(s):  
Matthew T. Woodhouse ◽  
Graham W. Mann ◽  
Kenneth S. Carslaw ◽  
Olivier Boucher

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