Compilation of quality controlled nutrient profiles from the Mediterranean Sea

In the last decades, a striking amount of hydrographic data, covering the most part of Mediterranean basin, have been generated by the efforts made to characterize the oceanography and ecology of the basin. On the other side, the improvement in technologies, and the consequent perfecting of sampling and analytical techniques, provided data even more reliable than in the past. Nutrient data enter fully in this context, but suffer of the fact of having been produced by a large number of uncoordinated research programs and of being often deficient in quality control, with data bases lacking of intercalibration. In this study we present a computational procedure based on robust statistical parameters and on the physical dynamic properties of the Mediterranean sea and its morphological characteristics, to partially overcome the above limits in the existing data sets. Through a data pre filtering based on the outlier analysis, and thanks to the subsequent shape analysis, the procedure identifies the inconsistent data and for each basin area identifies a characteristic set of shapes (vertical profiles). Rejecting all the profiles that do not follow any of the spotted shapes, the procedure identifies all the reliable profiles and allows us to obtain a data set that can be considered more internally consistent than the existing ones.近数十年来，为表征地中海盆地（Mediterranean basin）的海洋学与生态学特征，科研人员已生成覆盖该盆地绝大多数区域的海量水文数据（hydrographic data）。与此同时，技术的迭代升级与采样、分析技术的持续完善，使得所获数据的可靠性较以往显著提升。营养盐数据（nutrient data）虽纳入此类数据集范畴，但存在诸多固有缺陷：其数据源于大量分散独立的研究项目，且普遍缺乏质量控制，相关数据库未开展互校工作。本研究提出一种基于稳健统计参数（robust statistical parameters）、地中海海域物理动力特性及地形地貌特征的计算流程，以部分弥补现有数据集的上述局限。该流程首先依托异常值分析（outlier analysis）开展数据预滤波，结合后续的形状分析，识别出不合规的异常数据；并针对每个盆地分区，确定一组典型的形状特征（垂直剖面，vertical profiles）。通过剔除所有不符合上述典型形状的剖面，该流程可筛选出全部可靠的垂直剖面，最终得到相较于现有数据集内部一致性更优的数据集。