Intercomparison and validation of the mixed layer depth fields of global ocean syntheses
Intercomparison and validation of the mixed layer depth fields of global ocean syntheses
复制标题
全球海洋综合混合层深度场的比对和验证
DOI：
10.1007/s00382-015-2637-7
复制
发表时间：
2015
期刊：
影响因子：
4.6
通讯作者：
Tong Lee
中科院分区：
文献类型：
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作者：
T. Toyoda;Y. Fujii;T. Kuragano;M. Kamachi;Y. Ishikawa;S. Masuda;Kanako Sato;T. Awaji;F. Hernandez;N. Ferry;S. Guinehut;Matthew J. Martin;K. Peterson;S. Good;M. Valdivieso;K. Haines;A. Storto;S. Masina;A. Köhl;H. Zuo;M. Balmaseda;Yonghong Yin;Li Shi;O. Alves;Gregory C. Smith;You‐Soon Chang;G. Vernières;Xiaochun Wang;G. Forget;P. Heimbach;O. Wang;I. Fukumori;Tong Lee
摘要
对一系列主要海洋综合资料估算的全球海洋表面混合层深度场进行了相互比较和评价。与单剖面计算的参考MLD值相比，早春月平均和网格化剖面计算的MLD值有10-20 m的负偏差，这与较深混合层的再分层过程有关。剖面的垂直分辨率也影响MLD的估计。当使用位密度超过10 m值0.03 kg m−3的标准进行MLD估计时，MLD被低估约5-7（14-16）m，垂直分辨率为25（50）m。使用较大的标准（0.125 kg m−3）通常会减少低估。此外，积极的偏见大于100米，发现在冬季亚极地地区时，MLD标准的基础上使用的温度。再分析的偏差是由于模式误差和与同化方法之间的差异有关的误差。结果表明，这些误差通过系综平均被部分抵消。此外，在集合平均场的再分析的偏差是小于在仅观测分析。这在很大程度上归因于更高的分辨率的再分析。再分析的集合平均值的季节周期和年际变化的稳健再现表明集合平均MLD场用于调查和监测上层海洋过程的巨大潜力。
Abstract
Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10–20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5–7 (14–16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m−3 is used for the MLD estimation. Using the larger criterion (0.125 kg m−3) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.