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Author: Wagner, J. × Publisher: Göttingen : Copernicus GmbH ×

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    Evaluation of wake influence on high-resolution balloon-sonde measurements
    (Göttingen : Copernicus GmbH, 2019) Söder, J.; Gerding, M.; Schneider, A.; Dörnbrack, A.; Wilms, H.; Wagner, J.; Lübken, F.-J.
    Balloons are used for various in situ measurements in the atmosphere. On turbulence measurements from rising balloons there is a potential for misinterpreting wake-created fluctuations in the trail of the balloon for atmospheric turbulence. These wake effects have an influence on temperature and humidity measurements from radiosondes as well. The primary aim of this study is to assess the likelihood for wake encounter on the payload below a rising balloon. Therefore, we present a tool for calculating this probability based on radiosonde wind data. This includes a retrieval of vertical winds from the radiosonde and an uncertainty analysis of the wake assessment. Our wake evaluation tool may be used for any balloon-gondola distance and provides a significant refinement compared to existing assessments. We have analysed wake effects for various balloon-gondola distances applying atmospheric background conditions from a set of 30 radiosondes. For a standard radiosonde we find an average probability for wake encounter of 28 %, pointing out the importance of estimating wake effects on sounding balloons. Furthermore, we find that even millimetre-sized objects in the payload can have significant effects on high-resolution turbulence measurements, if they are located upstream of the turbulence sensor. © Author(s) 2019. This work is distributed under.
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    Spatial patterns of linear and nonparametric long-term trends in Baltic sea-level variability
    (Göttingen : Copernicus GmbH, 2012) Donner, R.V.; Ehrcke, R.; Barbosa, S.M.; Wagner, J.; Donges, J.F.; Kurths, J.
    The study of long-term trends in tide gauge data is important for understanding the present and future risk of changes in sea-level variability for coastal zones, particularly with respect to the ongoing debate on climate change impacts. Traditionally, most corresponding analyses have exclusively focused on trends in mean sea-level. However, such studies are not able to provide sufficient information about changes in the full probability distribution (especially in the more extreme quantiles). As an alternative, in this paper we apply quantile regression (QR) for studying changes in arbitrary quantiles of sea-level variability. For this purpose, we chose two different QR approaches and discuss the advantages and disadvantages of different settings. In particular, traditional linear QR poses very restrictive assumptions that are often not met in reality. For monthly data from 47 tide gauges from along the Baltic Sea coast, the spatial patterns of quantile trends obtained in linear and nonparametric (spline-based) frameworks display marked differences, which need to be understood in order to fully assess the impact of future changes in sea-level variability on coastal areas. In general, QR demonstrates that the general variability of Baltic sea-level has increased over the last decades. Linear quantile trends estimated for sliding windows in time reveal a wide-spread acceleration of trends in the median, but only localised changes in the rates of changes in the lower and upper quantiles.