@phdthesis{Samaras2016,
  author    = {Samaras, Stefanos},
  title     = {Microphysical retrieval of non-spherical aerosol particles using regularized inversion of multi-wavelength lidar data},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-396528},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 190},
  year      = {2016},
  abstract  = {Numerous reports of relatively rapid climate changes over the past century make a clear case of the impact of aerosols and clouds, identified as sources of largest uncertainty in climate projections. Earth's radiation balance is altered by aerosols depending on their size, morphology and chemical composition. Competing effects in the atmosphere can be further studied by investigating the evolution of aerosol microphysical properties, which are the focus of the present work. The aerosol size distribution, the refractive index, and the single scattering albedo are commonly used such properties linked to aerosol type, and radiative forcing. Highly advanced lidars (light detection and ranging) have reduced aerosol monitoring and optical profiling into a routine process. Lidar data have been widely used to retrieve the size distribution through the inversion of the so-called Lorenz-Mie model (LMM). This model offers a reasonable treatment for spherically approximated particles, it no longer provides, though, a viable description for other naturally occurring arbitrarily shaped particles, such as dust particles. On the other hand, non-spherical geometries as simple as spheroids reproduce certain optical properties with enhanced accuracy. Motivated by this, we adapt the LMM to accommodate the spheroid-particle approximation introducing the notion of a two-dimensional (2D) shape-size distribution. Inverting only a few optical data points to retrieve the shape-size distribution is classified as a non-linear ill-posed problem. A brief mathematical analysis is presented which reveals the inherent tendency towards highly oscillatory solutions, explores the available options for a generalized solution through regularization methods and quantifies the ill-posedness. The latter will improve our understanding on the main cause fomenting instability in the produced solution spaces. The new approach facilitates the exploitation of additional lidar data points from depolarization measurements, associated with particle non-sphericity. However, the generalization of LMM vastly increases the complexity of the problem. The underlying theory for the calculation of the involved optical cross sections (T-matrix theory) is computationally so costly, that would limit a retrieval analysis to an unpractical point. Moreover the discretization of the model equation by a 2D collocation method, proposed in this work, involves double integrations which are further time consuming. We overcome these difficulties by using precalculated databases and a sophisticated retrieval software (SphInX: Spheroidal Inversion eXperiments) especially developed for our purposes, capable of performing multiple-dataset inversions and producing a wide range of microphysical retrieval outputs. Hybrid regularization in conjunction with minimization processes is used as a basis for our algorithms. Synthetic data retrievals are performed simulating various atmospheric scenarios in order to test the efficiency of different regularization methods. The gap in contemporary literature in providing full sets of uncertainties in a wide variety of numerical instances is of major concern here. For this, the most appropriate methods are identified through a thorough analysis on an overall-behavior basis regarding accuracy and stability. The general trend of the initial size distributions is captured in our numerical experiments and the reconstruction quality depends on data error level. Moreover, the need for more or less depolarization points is explored for the first time from the point of view of the microphysical retrieval. Finally, our approach is tested in various measurement cases giving further insight for future algorithm improvements.},
  language  = {en}
}
@article{Paape2016,
  author    = {Paape, Dario L. J. F.},
  title     = {Filling the Silence: Reactivation, not Reconstruction},
  series = {Frontiers in psychology},
  volume    = {7},
  journal   = {Frontiers in psychology},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1664-1078},
  doi       = {10.3389/fpsyg.2016.00027},
  pages     = {18},
  year      = {2016},
  abstract  = {In a self-paced reading experiment, we investigated the processing of sluicing constructions ("sluices") whose antecedent contained a known garden path structure in German. Results showed decreased processing times for sluices with garden-path antecedents as well as a disadvantage for antecedents with non-canonical word order downstream from the ellipsis site. A post-hoc analysis showed the garden-path advantage also to be present in the region right before the ellipsis site. While no existing account of ellipsis processing explicitly predicted the results, we argue that they are best captured by combining a local antecedent mismatch effect with memory trace reactivation through reanalysis.},
  language  = {en}
}
@article{Paape2016,
  author    = {Paape, Dario L. J. F.},
  title     = {Filling the Silence},
  series = {Frontiers in psychology},
  volume    = {7},
  journal   = {Frontiers in psychology},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1664-1078},
  doi       = {10.3389/fpsyg.2016.00027},
  pages     = {1 -- 18},
  year      = {2016},
  abstract  = {In a self-paced reading experiment, we investigated the processing of sluicing constructions ("sluices") whose antecedent contained a known garden-path structure in German. Results showed decreased processing times for sluices with garden-path antecedents as well as a disadvantage for antecedents with non-canonical word order downstream from the ellipsis site. A post-hoc analysis showed the garden-path advantage also to be present in the region right before the ellipsis site. While no existing account of ellipsis processing explicitly predicted the results, we argue that they are best captured by combining a local antecedent mismatch effect with memory trace reactivation through reanalysis.},
  language  = {en}
}
@misc{Paape2016,
  author    = {Paape, Dario L. J. F.},
  title     = {Filling the Silence},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-90480},
  year      = {2016},
  abstract  = {In a self-paced reading experiment, we investigated the processing of sluicing constructions ("sluices") whose antecedent contained a known garden-path structure in German. Results showed decreased processing times for sluices with garden-path antecedents as well as a disadvantage for antecedents with non-canonical word order downstream from the ellipsis site. A post-hoc analysis showed the garden-path advantage also to be present in the region right before the ellipsis site. While no existing account of ellipsis processing explicitly predicted the results, we argue that they are best captured by combining a local antecedent mismatch effect with memory trace reactivation through reanalysis.},
  language  = {en}
}
@misc{MuellerBoeckmannKolgotinetal.2016,
  author    = {M{\"u}ller, Detlef and B{\"o}ckmann, Christine and Kolgotin, Alexei and Schneidenbach, Lars and Chemyakin, Eduard and Rosemann, Julia and Znak, Pavel and Romanov, Anton},
  title     = {Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {565},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41193},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-411934},
  pages     = {29},
  year      = {2016},
  abstract  = {We present a summary on the current status of two inversion algorithms that are used in EARLINET (European Aerosol Research Lidar Network) for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on a manually controlled inversion of optical data which allows for detailed sensitivity studies. The algorithms allow us to derive particle effective radius as well as volume and surface area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light absorption needs to be known with high accuracy. It is an extreme challenge to retrieve the real part with an accuracy better than 0.05 and the imaginary part with accuracy better than 0.005-0.1 or +/- 50 \%. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high-and low-absorbing aerosols. On the basis of a few exemplary simulations with synthetic optical data we discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work. One algorithm was used with the purpose of testing how well microphysical parameters can be derived if the real part of the complex refractive index is known to at least 0.05 or 0.1. The other algorithm was used to find out how well microphysical parameters can be derived if this constraint for the real part is not applied. The optical data used in our study cover a range of Angstrom exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types. We also tested aerosol scenarios that are considered highly unlikely, e.g. the lidar ratios fall outside the commonly accepted range of values measured with Raman lidar, even though the underlying microphysical particle properties are not uncommon. The goal of this part of the study is to test the robustness of the algorithms towards their ability to identify aerosol types that have not been measured so far, but cannot be ruled out based on our current knowledge of aerosol physics. We computed the optical data from monomodal logarithmic particle size distributions, i.e. we explicitly excluded the more complicated case of bimodal particle size distributions which is a topic of ongoing research work. Another constraint is that we only considered particles of spherical shape in our simulations. We considered particle radii as large as 7-10 mu m in our simulations where the Potsdam algorithm is limited to the lower value. We considered optical-data errors of 15\% in the simulation studies. We target 50\% uncertainty as a reasonable threshold for our data products, though we attempt to obtain data products with less uncertainty in future work.},
  language  = {en}
}