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Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model

Sahyoun, Maher LU ; Korsholm, Ulrik S. ; Sørensen, Jens H. ; Šantl-Temkiv, Tina ; Finster, Kai ; Gosewinkel, Ulrich and Nielsen, Niels W. (2017) In Atmospheric Environment 170. p.33-44
Abstract


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,... (More)


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.

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author
; ; ; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bacterial INP, Cloud ice, Global solar radiation, Heterogeneous ice nucleation, Numerical weather prediction model, Precipitation
in
Atmospheric Environment
volume
170
pages
12 pages
publisher
Elsevier
external identifiers
  • scopus:85030091379
ISSN
1352-2310
DOI
10.1016/j.atmosenv.2017.09.029
language
English
LU publication?
no
id
8c4a0f91-92e6-4df7-a1c3-b7566a377f6d
date added to LUP
2019-12-17 12:06:47
date last changed
2022-04-10 23:14:49
@article{8c4a0f91-92e6-4df7-a1c3-b7566a377f6d,
  abstract     = {{<p><br>
                            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<br>
                            <sup>−5</sup><br>
                             to 10<br>
                            <sup>−4</sup><br>
                            . 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.<br>
                        </p>}},
  author       = {{Sahyoun, Maher and Korsholm, Ulrik S. and Sørensen, Jens H. and Šantl-Temkiv, Tina and Finster, Kai and Gosewinkel, Ulrich and Nielsen, Niels W.}},
  issn         = {{1352-2310}},
  keywords     = {{Bacterial INP; Cloud ice; Global solar radiation; Heterogeneous ice nucleation; Numerical weather prediction model; Precipitation}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{33--44}},
  publisher    = {{Elsevier}},
  series       = {{Atmospheric Environment}},
  title        = {{Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model}},
  url          = {{http://dx.doi.org/10.1016/j.atmosenv.2017.09.029}},
  doi          = {{10.1016/j.atmosenv.2017.09.029}},
  volume       = {{170}},
  year         = {{2017}},
}