Processing of water level derived from water pressure data at the Time Series Station Spiekeroog
Processing of water level derived from water pressure data at the Time Series Station Spiekeroog
复制标题
处理从时间序列站 Spiekeroog 的水压数据得出的水位
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
O. Zielinski
中科院分区：
文献类型：
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作者：
L. Holinde;T. Badewien;J. Freund;E. Stanev;O. Zielinski
抽象。水位时间序列数据的质量随着高质量和低质量传感器数据的周期而变化很大。在本文中，我们提出的处理步骤，用于生成高质量的水位数据，在时间序列站（TSS）Spiekeroog测量的水压。TSS位于东弗里斯兰瓦登海（北海南部）Spiekeroog岛和朗格奥格岛之间的潮汐入口。处理步骤将涵盖传感器漂移、异常值识别、数据差距插值和质量控制。核心步骤是去除离群值。对于该过程，选择了0.25 m 10 min−1的绝对阈值，其在极端事件期间仍然保持水位增加和减少，如质量控制过程中所示。数据处理的第二个重要特征是间隙数据的插值，其以生成可信数据的高度确定性来完成。应用这些方法，处理了TSS水位信息的10年数据集（2002年12月至2012年12月），产生了7年时间序列（2005年至2011年）。补充数据见doi：10.1594/PANGAEA.843740。
Abstract. The quality of water level time series data strongly varies with periods of high- and low-quality sensor data. In this paper we are presenting the processing steps which were used to generate high-quality water level data from water pressure measured at the Time Series Station (TSS) Spiekeroog. The TSS is positioned in a tidal inlet between the islands of Spiekeroog and Langeoog in the East Frisian Wadden Sea (southern North Sea). The processing steps will cover sensor drift, outlier identification, interpolation of data gaps and quality control. A central step is the removal of outliers. For this process an absolute threshold of 0.25 m 10 min−1 was selected which still keeps the water level increase and decrease during extreme events as shown during the quality control process. A second important feature of data processing is the interpolation of gappy data which is accomplished with a high certainty of generating trustworthy data. Applying these methods a 10-year data set (December 2002–December 2012) of water level information at the TSS was processed resulting in a 7-year time series (2005–2011). Supplementary data are available at doi: 10.1594/PANGAEA.843740 .