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dc.contributor.authorMueller, Detlef
dc.contributor.authorChemyakin, Eduard V.
dc.contributor.authorKolgotin, Alexei V.
dc.contributor.authorFerrare, Richard A.
dc.contributor.authorHostetler, Chris A.
dc.contributor.authorRomanov, A.
dc.date.accessioned2019-08-07T00:29:58Z
dc.date.available2019-08-07T00:29:58Z
dc.date.issued2019-06-18
dc.identifier.citationMueller , D , Chemyakin , E V , Kolgotin , A V , Ferrare , R A , Hostetler , C A & Romanov , A 2019 , ' Automated, unsupervised inversion of multiwavelength lidar data with TiARA : Assessment of retrieval performance of microphysical parameters using simulated data ' , Applied Optics , vol. 58 , no. 18 , pp. 4981-5008 . https://doi.org/10.1364/AO.58.004981 , https://doi.org/10.1364/AO.58.004981
dc.identifier.issn0003-6935
dc.identifier.otherPURE: 16028527
dc.identifier.otherPURE UUID: 0cb75d67-5737-4a03-a273-d8bfe147e3c7
dc.identifier.otherScopus: 85068061578
dc.identifier.otherScopus: 85068061578
dc.identifier.urihttp://hdl.handle.net/2299/21545
dc.description.abstractWe evaluate the retrieval performance of the automated, unsupervised inversion algorithm, Tikhonov Advanced Regularization Algorithm (TiARA), which is used for the autonomous retrieval of microphysical parameters of anthropogenic and natural pollution particles. TiARA (version 1.0) has been developed in the past 10 years and builds on the legacy of a data-operator-controlled inversion algorithm used since 1998 for the analysis of data from multiwavelength Raman lidar. The development of TiARA has been driven by the need to analyze in (near) real time large volumes of data collected with NASA Langley Research Center's high-spectral-resolution lidar (HSRL-2). HSRL-2 was envisioned as part of the NASA Aerosols-Clouds-Ecosystems mission in response to the National Academy of Sciences (NAS) Decadal Study mission recommendations 2007. TiARA could thus also serve as an inversion algorithm in the context of a future space-borne lidar. We summarize key properties of TiARA on the basis of simulations with monomodal logarithmic-normal particle size distributions that cover particle radii from approximately 0.05 μm to 10 μm. The real and imaginary parts of the complex refractive index cover the range from nonabsorbing to highly light-absorbing pollutants. Our simulations include up to 25% measurement uncertainty. The goal of our study is to provide guidance with respect to technical features of future space-borne lidars, if such lidars will be used for retrievals of microphysical data products, absorption coefficients, and single-scattering albedo. We investigate the impact of two different measurement-error models on the quality of the data products.We also obtain for the first time, to the best of our knowledge, a statistical view on systematic and statistical uncertainties, if a large volume of data is processed. Effective radius is retrieved to 50% accuracy for 58% of cases with an imaginary part up to 0.01i and up to 100% of cases with an imaginary part of 0.05i. Similarly, volume concentration, surface-area concentration, and number concentrations are retrieved to 50% accuracy in 56%-100% of cases, 99%-100% of cases, and 54%-87% of cases, respectively, depending on the imaginary part. The numbers represent measurement uncertainties of up to 15%. If we target 20% retrieval accuracy, the numbers of cases that fall within that threshold are 36%-76% for effective radius, 36%-73% for volume concentration, 98%-100% for surface-area concentration, and 37%-61% for number concentration. That range of numbers again represents a spread in results for different values of the imaginary part. At present, we obtain an accuracy of (on average) 0.1 for the real part. A case study from the ORCALES field campaign is used to illustrate data products obtained with TiARA.en
dc.format.extent28
dc.language.isoeng
dc.relation.ispartofApplied Optics
dc.subjectAtomic and Molecular Physics, and Optics
dc.subjectEngineering (miscellaneous)
dc.subjectElectrical and Electronic Engineering
dc.titleAutomated, unsupervised inversion of multiwavelength lidar data with TiARA : Assessment of retrieval performance of microphysical parameters using simulated dataen
dc.contributor.institutionCentre for Atmospheric and Climate Physics Research
dc.contributor.institutionSchool of Physics, Astronomy and Mathematics
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85068061578&partnerID=8YFLogxK
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1364/AO.58.004981
rioxxterms.typeJournal Article/Review


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