用一张图概括三重搭配分析的多个方面

L. Siu, Xubin Zeng, A. Sorooshian, Brian Cairns, R. Ferrare, J. Hair, C. Hostetler, D. Painemal, J. Schlosser
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引用次数: 0

摘要

随着全球观测网络的不断扩大,预计我们将对来自多个共用仪器的温度等地球物理变量记录进行例行分析。在这种情况下,验证数据集并非易事,因为每个观测系统都有自己的偏差和噪声。三重定位是一个通用的统计框架,用于估算三个或更多基于观测的数据集的误差特征。在三重同位分析中,通常会报告几个指标,但传统的多面板图并不是显示信息的最有效方式。为连接三重同位理论中的关键术语,我们推导出了一个新的误差方差公式。根据该公式设计了一个图表,以方便对观测数据进行三重配位分析,并使用最近的大西洋西部气溶胶云气象学相互作用实验(ACTIVATE)中的三个气溶胶光学深度数据集进行了说明。考虑到误差方差和相关系数,还得出了基于观测的技能评分,以评估三个数据集的质量。讨论了若干应用,并提供了示例绘图例程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Summarizing multiple aspects of triple collocation analysis in a single diagram
With the ongoing expansion of global observation networks, it is expected that we shall routinely analyze records of geophysical variables such as temperature from multiple collocated instruments. Validating datasets in this situation is not a trivial task because every observing system has its own bias and noise. Triple collocation is a general statistical framework to estimate the error characteristics in three or more observational-based datasets. In a triple colocation analysis, several metrics are routinely reported but traditional multiple-panel plots are not the most effective way to display information. A new formula of error variance is derived for connecting the key terms in the triple collocation theory. A diagram based on this formula is devised to facilitate triple collocation analysis of any data from observations, as illustrated using three aerosol optical depth datasets from the recent Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). An observational-based skill score is also derived to evaluate the quality of three datasets by taking into account both error variance and correlation coefficient. Several applications are discussed and sample plotting routines are provided.
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