DOI: 10.1016/j.atmosenv.2017.09.029
Scopus记录号: 2-s2.0-85030091379
论文题名: Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model
作者: Sahyoun M ; , Korsholm U ; S ; , Sørensen J ; H ; , Šantl-Temkiv T ; , Finster K ; , Gosewinkel U ; , Nielsen N ; W
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 170 起始页码: 33
结束页码: 44
语种: 英语
英文关键词: Bacterial INP
; Cloud ice
; Global solar radiation
; Heterogeneous ice nucleation
; Numerical weather prediction model
; Precipitation
Scopus关键词: Drops
; Dust
; Forecasting
; Nucleation
; Numerical models
; Precipitation (chemical)
; Precipitation (meteorology)
; Solar radiation
; Weather forecasting
; Enhancement factor
; Global solar radiation
; Ice nucleation
; Ice nucleation rates
; Numerical weather prediction models
; Precipitation formation
; Small concentration
; Total precipitation
; Ice
; ice
; air temperature
; bacterium
; climate prediction
; cloud condensation nucleus
; heterogeneity
; melting
; nucleation
; numerical method
; perturbation
; precipitation (climatology)
; solar radiation
; weather forecasting
; Article
; bacterial ice nucleating particle
; bacterium
; cloud
; controlled study
; forecasting
; melting point
; nonhuman
; precipitation
; prediction
; priority journal
; quantitative study
; sensitivity analysis
; solar radiation
; surface property
; Bacteria (microorganisms)
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Bacterial ice-nucleating particles (INP) have the ability to facilitate ice nucleation from super-cooled cloud droplets at temperatures just below the melting point. Bacterial INP have been detected in cloud water, precipitation, and dry air, hence they may have an impact on weather and climate. In modeling studies, the potential impact of bacteria on ice nucleation and precipitation formation on global scale is still uncertain due to their small concentration compared to other types of INP, i.e. dust. Those earlier studies did not account for the yet undetected high concentration of nanoscale fragments of bacterial INP, which may be found free or attached to soil dust in the atmosphere. In this study, we investigate the sensitivity of modeled cloud ice, precipitation and global solar radiation in different weather scenarios to changes in the fraction of cloud droplets containing bacterial INP, regardless of their size. For this purpose, a module that calculates the probability of ice nucleation as a function of ice nucleation rate and bacterial INP fraction was developed and implemented in a numerical weather prediction model. The threshold value for the fraction of cloud droplets containing bacterial INP needed to produce a 1% increase in cloud ice was determined at 10−5 to 10−4. We also found that increasing this fraction causes a perturbation in the forecast, leading to significant differences in cloud ice and smaller differences in convective and total precipitation and in net solar radiation reaching the surface. These effects were most pronounced in local convective events. Our results show that bacterial INP can be considered as a trigger factor for precipitation, but not an enhancement factor. © 2017 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82492
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Research and Development, Danish Meteorological Institute, Copenhagen, Denmark; Department of Bioscience, Microbiology Section, Aarhus University, Aarhus, Denmark; Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark; Department of Environmental Science, Aarhus University, Roskilde, Denmark; Observatoire de Physique du Globe de Clermont-Ferrand, Laboratoire de Météorologie Physique (LaMP), University of Clermont Auvergne, Aubiere, France
Recommended Citation:
Sahyoun M,, Korsholm U,S,et al. Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model[J]. Atmospheric Environment,2017-01-01,170