均质化(气候)
环境科学
分位数
不连续性分类
气候变化
遥感
计算机科学
气象学
气候学
数据挖掘
数学
统计
地质学
地理
海洋学
数学分析
生物多样性
生物
生态学
作者
Wolfgang Preimesberger,Tracy Scanlon,Chun‐Hsu Su,A. Gruber,Wouter Dorigo
标识
DOI:10.1109/tgrs.2020.3012896
摘要
The European Space Agency’s Climate Change Initiative (ESA CCI) Soil Moisture (SM) COMBINED product is a more than 40-year-long data record on global SM for climate studies and applications. It merges SM observations derived from multiple active and passive satellite remote sensing instruments in the microwave domain. Differences in sensor characteristics (such as frequency or polarization) can cause structural breaks in the product, which are not completely removed during the merging process. These artificially caused discontinuities can adversely affect studies using the long-term data set. In this article, we compare three adjustment methods in terms of reducing the number of detected breaks in the SM record. We investigate their impact on the data with multiple validation metrics. Their potential (negative) influence is examined by comparing trends in the data before and after homogenization. We find that all three presented methods can reduce the number of detected breaks in ESA CCI SM. Differences between the methods mainly concern their ability to handle inhomogeneities in variance. Evaluation of the corrected data shows the limited impact of homogenization in terms of quantitative validation metrics. Changes in SM trends due to removing breaks are found in some areas. We find that break correction overall improves the already rather homogeneous data set while preserving its climate describing characteristics. Quantile category matching is identified as the preferred method in terms of correcting breaks in ESA CCI SM.
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