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Precipitation enhancement in stratocumulus clouds through airbourne seeding: sensitivity analysis by UCLALES–SALSA

Authors: Juha Tonttila; Ali Afzalifar; Harri Kokkola; Tomi Raatikainen; Hannele Korhonen; Sami Romakkaniemi;

Precipitation enhancement in stratocumulus clouds through airbourne seeding: sensitivity analysis by UCLALES–SALSA

Abstract

Abstract. Artificial enhancement of precipitation via hygroscopic cloud seeding is investigated with a numerical large-eddy simulation model coupled with a spectral aerosol-cloud microphysics module. We focus our investigation on marine stratocumulus clouds and evaluate our model results by comparing them with recently published results from field observations. Creating multiple realizations of a single cloud event with the model provides a robust method to detect and attribute the seeding effects, which reinforces the analysis based on experimental data. Owing to the detailed representation of aerosol-cloud interactions, our model successfully reproduces the microphysical signatures attributed to the seeding, that were also seen in the observations. Moreover, the model simulations show up to a 2–3 fold increase in the precipitation flux due to the seeding, depending on the seeding rate and injection strategy. However, our simulations suggest that a relatively high seeding particle emission rate is needed for a substantial increase in the precipitation yield, as compared with the estimated seeding concentrations from the field campaign. In practical applications, the seeding aerosol is often produced by flare burning. It is speculated, that the required amount of large seeding particles suggested by our results could pose a technical challenge to the flare-based approach.

Country
Finland
Keywords

Chemistry, Physics, QC1-999, QD1-999

  • BIP!
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    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green
gold