scholarly journals The effect of organic compounds on the growth rate of cloud droplets in marine and forest settings

2008 ◽  
Vol 8 (19) ◽  
pp. 5869-5887 ◽  
Author(s):  
N. C. Shantz ◽  
W. R. Leaitch ◽  
L. Phinney ◽  
M. Mozurkewich ◽  
D. Toom-Sauntry

Abstract. Organic matter represents an important fraction of the fine particle aerosol, yet our knowledge of the roles of organics in the activation of aerosol particles into cloud droplets is poor. A cloud condensation nucleus (CCN) counter is used to examine the relative growth rates of cloud droplets for case studies from field measurements on the North Pacific Ocean and in a coniferous forest. A model of the condensational growth of water droplets, on particles dissolving according to their solubility in water, is used to simulate the initial scattering of the droplets as they grow in the CCN counter. Simulations of the growth rates of fine particles sampled in the marine boundary layer of the North Pacific Ocean shows no evidence of natural marine organic material contributing to the CCN water uptake but there is an indication of an influence from organics from diesel ship emissions on the size distribution of sulphate and the ability of these particles to act as CCN. Simulations of the observations of water uptake on biogenic organic aerosol particles sampled in a coniferous forest indicate an impact of the organic on the water uptake rates, but one that is still smaller than that of pure sulphate. The existence of organics becomes important in determining the water uptake as the organic mass increases relative to sulphate. The values of the organic component of the hygroscopicity parameter κ that describes the CCN activity were found to be negligible for the marine particles and 0.02–0.05 for the forest particles.

2008 ◽  
Vol 8 (2) ◽  
pp. 8193-8242 ◽  
Author(s):  
N. C. Shantz ◽  
W. R. Leaitch ◽  
L. Phinney ◽  
D. Toom-Sauntry ◽  
M. Mozurkewich

Abstract. Organic matter represents an important fraction of the fine particle aerosol, yet our knowledge of the roles of organics in the activation of aerosol particles into cloud droplets is poor. A cloud condensation nucleus (CCN) counter is used to examine the relative growth rates of cloud droplets for case studies from field measurements on the North Pacific Ocean and in a coniferous forest. A model of the condensational growth of water droplets, on particles dissolving according to their solubility in water, is used to simulate the initial scattering of the droplets as they grow in the CCN counter. Simulations of the growth rates of fine particles sampled in the marine boundary layer of the North Pacific Ocean indicate that the main influence of the marine organic material on the water uptake rate is from its effect on the size distribution of the sulphate. Simulations of the observations of water uptake on biogenic organic aerosol particles sampled in a coniferous forest indicate an impact of the organic on the water uptake rates, but one that is still smaller than that of pure sulphate. The solubility of the organic becomes an important factor in determining the water uptake as the organic mass increases relative to sulphate. The values of the organic component of the hygroscopicity parameter κ that describes the CCN activity were found to be negligible for the marine particles and 0.02–0.05 for the forest particles.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.


2021 ◽  
Author(s):  
R. J. David Wells ◽  
Veronica A. Quesnell ◽  
Robert L. Humphreys ◽  
Heidi Dewar ◽  
Jay R. Rooker ◽  
...  

2010 ◽  
Vol 37 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Robert H. Byrne ◽  
Sabine Mecking ◽  
Richard A. Feely ◽  
Xuewu Liu

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