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Spatial patterns of linear and nonparametric long-term trends in Baltic sea-level variability

机译：波罗的海海平面变化的线性和非参数长期趋势的空间格局

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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.
机译：研究潮汐量表数据的长期趋势，对于了解沿海地区海平面变化的当前和未来风险非常重要，尤其是在有关气候变化影响的辩论中。传统上，大多数相应的分析仅专注于平均海平面趋势。但是，此类研究无法提供有关完整概率分布（尤其是在更极端分位数中）变化的足够信息。作为替代方案，在本文中，我们将分位数回归（QR）用于研究海平面变化的任意分位数的变化。为此，我们选择了两种不同的QR方法，并讨论了不同设置的优缺点。特别是，传统的线性QR提出了非常严格的假设，而这些假设通常在现实中是无法满足的。对于波罗的海沿岸47个潮汐仪的月度数据，在线性和非参数（基于样条）框架中获得的分位数趋势的空间模式显示出明显的差异，需要充分理解这些差异，以便全面评估未来变化的影响沿海地区的海平面变化。总的来说，QR表明过去几十年来波罗的海海平面的总体变化性有所增加。随时间推移滑动窗口估计的线性分位数趋势显示中位数趋势的广泛加速，但较低和较高分位数的变化率仅发生局部变化。

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