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首页> 外文期刊>Advances in Adaptive Data Analysis >EOF-MSE ADAPTIVE METHOD TO ASSESS AN ACID DEPOSITION MONITORING NETWORK OVER ALBERTA, CANADA
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EOF-MSE ADAPTIVE METHOD TO ASSESS AN ACID DEPOSITION MONITORING NETWORK OVER ALBERTA, CANADA

机译：EOF-MSE自适应方法评估加拿大艾伯塔省酸沉积物监测网络

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摘要

This study provides an adaptive data analysis method that assesses Alberta's acid deposition monitoring network of 9 stations and the relative importance of each station. The method is based on the assessment of the mean square error (MSE) of sampling expressed in terms of empirical orthogonal functions (EOF). The annual potential acid input (PAI) data of the 9 stations over Alberta, Canada are used in this study. The patterns of the EOFs and PCs (principal components) are analyzed to reflect the PAI's spatial-temporal distribution properties. The definition and minimization of the MSE are the basis for our assessment method. The mean PAI field in the period of 1993-2006 and the PAI fields of individual years demonstrate a strong spatial inhomogeneity of the PAI field over Alberta. The PAI level is high in the Red Deer-Calgary-Kananaskis corridor. Our optimal analysis indicates that the 9-station network is, in general, adequate in monitoring the overall PAI in Alberta. The network results in a small root-mean-squareerror/standard-deviation ratio (5.6%), which demonstrates the reasonable effectiveness of the network. In the period of 14 years (1993-2006), there were only three years (1993, 1998, and 2002) during which the PAI values were higher than the monitoring load of 0.17 [keq H~+ ha~(-1)yr~(-1)] at three locations: Red Deer, Calgary, and Kananaskis. According to a station's contribution to the reduction of sampling error, the descending order of importance for the 9 stations is as follows: Beaverlodge, Fort Chipewyan, Suffield, Red Deer, Cold Lake, Kananaskis, Calgary, Fort Vermilion, and Fort McMurray.
机译：这项研究提供了一种自适应数据分析方法，可评估9个站点的艾伯塔省酸沉降监测网络以及每个站点的相对重要性。该方法基于对以经验正交函数（EOF）表示的采样均方误差（MSE）的评估。本研究使用加拿大艾伯塔省9个站点的年度潜在酸输入（PAI）数据。对EOF和PC（主要成分）的模式进行了分析，以反映PAI的时空分布特性。 MSE的定义和最小化是我们评估方法的基础。 1993年至2006年期间的平均PAI场和个别年份的PAI场显示了艾伯塔省PAI场的强烈空间非均质性。雷德迪尔-卡尔加里-卡纳纳斯基斯走廊的PAI水平很高。我们的最佳分析表明，九站网络通常足以监控艾伯塔省的整个PAI。该网络导致均方根误差/标准偏差比率（5.6％）小，这表明该网络具有合理的有效性。在14年（1993年至2006年）期间，只有3年（1993年，1998年和2002年）的PAI值高于0.17 [keq H〜+ ha〜（-1）yr 〜（-1）]位于三个位置：Red Deer，卡尔加里和Kananaskis。根据一个站点对减少采样误差的贡献，这9个站点的重要性从高到低依次为：Beaverlodge，Chivewyan堡，Suffield，Red Deer，Cold Lake，Kananaskis，卡尔加里，Fort Vermilion和Fort McMurray。

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