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Now showing 1 - 10 of 13
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    Organic aerosol concentration and composition over Europe: Insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis
    (München : European Geopyhsical Union, 2014) Fountoukis, C.; Megaritis, A.G.; Skyllakou, K.; Charalampidis, P.E.; Pilinis, C.; van der Gon, H.A.C. Denier; Crippa, M.; Canonaco, F.; Mohr, C.; Prévôt, A.S.H.; Allan, J.D.; Poulain, L.; Petäjä, T.; Tiitta, P.; Carbone, S.; Kiendler-Scharr, A.; Nemitz, E.; O'Dowd, C.; Swietlicki, E.; Pandis, S.N.
    A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.
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    A new method to determine the mixing state of light absorbing carbonaceous using the measured aerosol optical properties and number size distributions
    (München : European Geopyhsical Union, 2012) Ma, N.; Zhao, C.S.; Müller, T.; Cheng, Y.F.; Liu, P.F.; Deng, Z.Z.; Xu, W.Y.; Ran, L.; Nekat, B.; van Pinxteren, D.; Gnauk, T.; Müller, K.; Herrmann, H.; Yan, P.; Zhou, X.J.; Wiedensohler, A.
    In this paper, the mixing state of light absorbing carbonaceous (LAC) was investigated with a two-parameter aerosol optical model and in situ aerosol measurements at a regional site in the North China Plain (NCP). A closure study between the hemispheric backscattering fraction (HBF) measured by an integrating nephelometer and that calculated with a modified Mie model was conducted. A new method was proposed to retrieve the ratio of the externally mixed LAC mass to the total mass of LAC (rext-LAC) based on the assumption that the ambient aerosol particles were externally mixed and consisted of a pure LAC material and a core-shell morphology in which the core is LAC and the shell is a less absorbing material. A Monte Carlo simulation was applied to estimate the overall influences of input parameters of the algorithm to the retrieved rext-LAC. The diurnal variation of rext-LAC was analyzed and the PartMC-MOSAIC model was used to simulate the variation of the aerosol mixing state. Results show that, for internally mixed particles, the assumption of core-shell mixture is more appropriate than that of homogenous mixture which has been widely used in aerosol optical calculations. A significant diurnal pattern of the retrieved rext-LAC was found, with high values during the daytime and low values at night. The consistency between the retrieved rext-LAC and the model results indicates that the diurnal variation of LAC mixing state is mainly caused by the diurnal evolution of the mixing layer.
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    Detection of convective initiation using Meteosat SEVIRI: Implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM
    (München : European Geopyhsical Union, 2013) Merk, D.; Zinner, T.
    In this paper a new detection scheme for convective initiation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting CI with geostationary satellite data. It uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared (IR) criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one high-resolution visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims to identify the typical development of quickly developing convective cells in an early stage. The different criteria include time trends of the 10.8 IR channel, and IR channel differences, as well as their time trends. To provide the trend fields an optical-flow-based method is used: the pyramidal matching algorithm, which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM, and is verified for seven days which comprise different weather situations in central Europe. Contrasted with the original early-stage detection scheme of Cb-TRAM, skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for the synoptic class "cold air" masses.
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    A fast and easy-to-implement inversion algorithm for mobility particle size spectrometers considering particle number size distribution information outside of the detection range
    (München : European Geopyhsical Union, 2014) Pfeifer, S.; Birmili, W.; Schladitz, A.; Müller, T.; Nowak, A.; Wiedensohler, A.
    Multiple-charge inversion is an essential procedure to convert the raw mobility distributions recorded by mobility particle size spectrometers, such as the DMPS or SMPS (differential or scanning mobility particle sizers), into true particle number size distributions. In this work, we present a fast and easy-to-implement multiple-charge inversion algorithm with sufficient precision for atmospheric conditions, but extended functionality. The algorithm can incorporate size distribution information from sensors that measure beyond the upper sizing limit of the mobility spectrometer, such as an aerodynamic particle sizer (APS) or an optical particle counter (OPC). This feature can considerably improve the multiple-charge inversion result in the upper size range of the mobility spectrometer, for example, when substantial numbers of coarse particles are present. The program also yields a continuous size distribution from both sensors as an output. The algorithm is able to calculate the propagation of measurement errors, such as those based on counting statistics, into on the final particle number size distribution. As an additional aspect, the algorithm can perform all inversion steps under the assumption of non-spherical particle shape, including constant or size-dependent shape factors.
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    Aerosol hygroscopicity parameter derived from the light scattering enhancement factor measurements in the North China Plain
    (Göttingen : Copernicus, 2014) Chen, J.; Zhao, C.S.; Ma, N.; Yan, P.
    The relative humidity (RH) dependence of aerosol light scattering is an essential parameter for accurate estimation of the direct radiative forcing induced by aerosol particles. Because of insufficient information on aerosol hygroscopicity in climate models, a more detailed parameterization of hygroscopic growth factors and resulting optical properties with respect to location, time, sources, aerosol chemistry and meteorology are urgently required. In this paper, a retrieval method to calculate the aerosol hygroscopicity parameter, κ, is proposed based on the in situ measured aerosol light scattering enhancement factor, namely f(RH), and particle number size distribution (PNSD) obtained from the HaChi (Haze in China) campaign. Measurements show that f(RH) increases sharply with increasing RH, and that the time variance of f(RH) is much greater at higher RH. A sensitivity analysis reveals that the f(RH) is more sensitive to the aerosol hygroscopicity than PNSD. f(RH) for polluted cases is distinctly higher than that for clean periods at a specific RH. The derived equivalent κ, combined with the PNSD measurements, is applied in the prediction of the cloud condensation nuclei (CCN) number concentration. The predicted CCN number concentration with the derived equivalent κ agrees well with the measured ones, especially at high supersaturations. The proposed calculation algorithm of κ with the f(RH) measurements is demonstrated to be reasonable and can be widely applied.
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    Digital IIR filters design using differential evolution algorithm with a controllable probabilistic population size
    (San Francisco, CA : Public Library of Science (PLoS), 2012) Zhu, W.; Fang, J.-A.; Tang, Y.; Zhang, W.; Du, W.
    Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive.
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    Polymer Brushes under High Load
    (San Francisco, CA : Public Library of Science, 2013) Balko, S.M.; Kreer, T.; Costanzo, P.J.; Patten, T.E.; Johner, A.; Kuhl, T.L.; Marques, C.M.
    Polymer coatings are frequently used to provide repulsive forces between surfaces in solution. After 25 years of design and study, a quantitative model to explain and predict repulsion under strong compression is still lacking. Here, we combine experiments, simulations, and theory to study polymer coatings under high loads and demonstrate a validated model for the repulsive forces, proposing that this universal behavior can be predicted from the polymer solution properties.
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    Change in the embedding dimension as an indicator of an approaching transition
    (San Francisco, CA : Public Library of Science (PLoS), 2014) Neuman, Y.; Marwan, N.; Cohen, Y.
    Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.
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    Long-term trends in the ionospheric E and F1 regions
    (Göttingen : Copernicus, 2008) Bremer, J.
    Ground based ionosonde measurements are the most essential source of information about long-term variations in the ionospheric E and F1 regions. Data of such observations have been derived at many different ionospheric stations all over the world some for more than 50 years. The standard parameters foE, h'E, and foF1 are used for trend analyses in this paper. Two main problems have to be considered in these analyses. Firstly, the data series have to be homogeneous, i.e. the observations should not be disturbed by artificial steps due to technical reasons or changes in the evaluation algorithm. Secondly, the strong solar and geomagnetic influences upon the ionospheric data have carefully to be removed by an appropriate regression analysis. Otherwise the small trends in the different ionospheric parameters cannot be detected. The trends derived at individual stations differ markedly, however their dependence on geographic or geomagnetic latitude is only small. Nevertheless, the mean global trends estimated from the trends at the different stations show some general behaviour (positive trends in foE and foF1, negative trend in h'E) which can at least qualitatively be explained by an increasing atmospheric greenhouse effect (increase of CO2 content and other greenhouse gases) and decreasing ozone values. The positive foE trend is also in qualitative agreement with rocket mass spectrometer observations of ion densities in the E region. First indications could be found that the changing ozone trend at mid-latitudes (before about 1979, between 1979 until 1995, and after about 1995) modifies the estimated mean foE trend.
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    Constructing proxy records from age models (COPRA)
    (München : European Geopyhsical Union, 2012) Breitenbach, S.F.M.; Rehfeld, K.; Goswami, B.; Baldin, J.U.L.; Ridley, H.E.; Kennett, D.J.; Prufer, K.M.; Aquino, V.V.; Asmerom, Y.; Polyak, V.J.; Cheng, H.; Kurths, J.; Marwan, N.
    Reliable age models are fundamental for any palaeoclimate reconstruction. Available interpolation procedures between age control points are often inadequately reported, and very few translate age uncertainties to proxy uncertainties. Most available modeling algorithms do not allow incorporation of layer counted intervals to improve the confidence limits of the age model in question. We present a framework that allows detection and interactive handling of age reversals and hiatuses, depth-age modeling, and proxy-record reconstruction. Monte Carlo simulation and a translation procedure are used to assign a precise time scale to climate proxies and to translate dating uncertainties to uncertainties in the proxy values. The presented framework allows integration of incremental relative dating information to improve the final age model. The free software package COPRA1.0 facilitates easy interactive usage.