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Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data

机译:评估卫星多任务海洋颜色气候数据记录的适用性:应用于OC-CCI叶绿素a数据的协议

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摘要

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll-a (Chla) data and to assess the fitness-for-purpose of multi-mission Chla products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t-test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chla data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012–2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chla data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research.
机译:在这项工作中,趋势估算被用作指标,以比较不同卫星叶绿素a(Chla)数据的多年变化性,并评估多任务Chla产品作为气候数据记录(CDR)的适用性。在单任务产品没有虚假的时间假象且可以用作基准时间序列的假设下,多任务CDR在重现其各自周期时,应重现单任务序列观察到的主要趋势模式。这项研究引入并应用了定量指标,以比较来自不同数据记录的趋势分布。首先,权变矩阵比较以二进制类别(如存在,重要性和趋势迹象)表示的与两个卫星产品相关的趋势诊断。权变矩阵可以通过诸如Cohenκ指数之类的度量标准进一步总结,该指数对两种诊断分布之间的总体一致性进行评分。通过趋势斜率之间差异的分布,可以更定量地度量趋势之间的差异。第三,量化两个趋势估计差异程度的t检验的显着性水平P的图提供了统计上,空间上可分辨的评估。拟议的方法应用于多任务海洋颜色-气候变化倡议(OC-CCI)Chla数据。与OC-CCI数据相关的趋势分布与单任务产品之间的一致性通常看起来与单任务产品进行比较时一样好。由于分析时间已延长至2012年至2015年,因此协议水平趋于下降,这可能至少部分是由于Aqua机载MODIS传感器的老化所致。另一方面,OC-CCI系列在2012-2015年短期内显示的趋势与VIIRS所观察到的趋势非常一致。这些结果总体上表明OC-CCI Chla数据可以用于多年时间序列分析(包括趋势检测),但是如果包括最近几年,尤其是在中部热带太平洋地区,则需要谨慎行事。该研究还回顾了创建适合气候研究的多任务海洋颜色数据记录所带来的挑战。

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