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Träfflista för sökning "WFRF:(Stier P.) srt2:(2010-2014)"

Search: WFRF:(Stier P.) > (2010-2014)

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1.
  • Mann, G. W., et al. (author)
  • Intercomparison and evaluation of global aerosol microphysical properties among AeroCom models of a range of complexity
  • 2014
  • In: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 14:9, s. 4679-4713
  • Journal article (peer-reviewed)abstract
    • Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e. g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
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2.
  • Kassemeyer, Stephan, et al. (author)
  • Femtosecond free-electron laser x-ray diffraction data sets for algorithm development
  • 2012
  • In: Optics Express. - 1094-4087. ; 20:4, s. 4149-4158
  • Journal article (peer-reviewed)abstract
    • We describe femtosecond X-ray diffraction data sets of viruses and nanoparticles collected at the Linac Coherent Light Source. The data establish the first large benchmark data sets for coherent diffraction methods freely available to the public, to bolster the development of algorithms that are essential for developing this novel approach as a useful imaging technique. Applications are 2D reconstructions, orientation classification and finally 3D imaging by assembling 2D patterns into a 3D diffraction volume.
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3.
  • Yoon, Chun Hong, et al. (author)
  • Unsupervised classification of single-particle X-ray diffraction snapshots by spectral clustering
  • 2011
  • In: Optics Express. - 1094-4087. ; 19:17, s. 16542-16549
  • Journal article (peer-reviewed)abstract
    • Single-particle experiments using X-ray Free Electron Lasers produce more than 10(5) snapshots per hour, consisting of an admixture of blank shots (no particle intercepted), and exposures of one or more particles. Experimental data sets also often contain unintentional contamination with different species. We present an unsupervised method able to sort experimental snapshots without recourse to templates, specific noise models, or user-directed learning. The results show 90% agreement with manual classification.
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