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dc.contributor.authorTesche, Matthias
dc.date.accessioned2019-09-10T00:07:55Z
dc.date.available2019-09-10T00:07:55Z
dc.date.issued2019-09-09
dc.identifier.citationTesche , M 2019 , ' Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements ' , Atmospheric Chemistry and Physics , vol. 19 , no. 17 , acp-19-11315-2019 , pp. 11315–11342 . https://doi.org/10.5194/acp-19-11315-2019
dc.identifier.issn1680-7316
dc.identifier.otherPURE: 17355578
dc.identifier.otherPURE UUID: 1f5bdd15-7650-47b2-8f03-201f8879b964
dc.identifier.otherScopus: 85072131232
dc.identifier.urihttp://hdl.handle.net/2299/21665
dc.description.abstractAerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,dry with an uncertainty of 20 % to 40 % and Sdry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range −50 to −33 ∘C) agree within 1 order of magnitude with the in situ observations of nINP; thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range −35 to −9 ∘C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot.en
dc.format.extent28
dc.language.isoeng
dc.relation.ispartofAtmospheric Chemistry and Physics
dc.rightsOpen
dc.subjectAtmospheric Science
dc.titleRetrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurementsen
dc.contributor.institutionSchool of Physics, Astronomy and Mathematics
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85072131232&partnerID=8YFLogxK
dc.relation.schoolSchool of Physics, Astronomy and Mathematics
dc.description.versiontypeFinal Published version
dcterms.dateAccepted2019-09-09
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.5194/acp-19-11315-2019
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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