Monthly climatology of the upper ocean pycnocline

the upper ocean pycnocline (uop) monthly climatology is based on the isas20 argo dataset containing argo and deep-argo temperature and salinity profiles on the period 2002-2020. regardless of the season, the uop is defined as the shallowest significant stratification peak captured by the method described in sérazin et al. (2022), whose detection threshold is proportional to the standard deviation of the stratification profile.the three main characteristics of the uop are provided -- intensity, depth and thickness -- along with hydrographic variables at the upper and lower edges of the pycnocline, the turner angle and density ratio at the depth of the uop. a stratification index (si) that evaluates the amount of buoyancy required to destratify the upper ocean down to a certain depth, is also included. when evaluated at the bottom of the uop, this gives the upper ocean stratification index (uosi) as discussed in sérazin et al. (2022). three mixed layer depth variables are also included in this dataset, including the one using the classic density threshold of 0.03 kg.m-3, along with the minimum of these mld variables.several statistics of the uop characteristics and the associated quantities are available in 2°×2° bins for each month of the year, whose results were smoothed using a diffusive gaussian filter with a 500 km scale. uop characteristics are also available for each profile, with all the profiles sorted in one file per month.

该上层海洋密度跃层（UOP）月度气候学数据集基于ISAS20 Argo数据集，该数据集包含2002-2020年期间的Argo和Deep Argo温度与盐度剖面。无论季节如何，UOP被定义为通过Sérazin等（2022）所述方法捕获的最浅显著层结峰值，其检测阈值与层结剖面的标准差成比例。UOP的三个主要特征——强度、深度和厚度——以及密度跃层上下边缘的海洋学变量、UOP深度的Turner角和密度比均得到提供。此外，还包括一个层结指数（SI），该指数评估将上层海洋去层结至特定深度所需的浮力量。当在UOP底部进行评估时，该指数即为Sérazin等（2022）所讨论的上层海洋层结指数（UOSI）。数据集中还包含了三个混合层深度变量，包括使用经典密度阈值0.03 kg.m-3的变量，以及这些混合层深度变量的最小值。UOP特征及其相关量的多个统计量以每年每月的2°×2°网格形式提供，其结果使用500 km尺度的扩散高斯滤波器进行了平滑处理。UOP特征还针对每个剖面提供，所有剖面按每月一个文件进行排序。