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全球海洋综合温跃层梯度、等温层深度和其他上层海洋参数。

Global ocean synoptic thermocline gradient, isothermal-layer depth, and other upper ocean parameters.

机构信息

Naval Ocean Analysis and Prediction Laboratory, Department of Oceanography, Naval Postgraduate School, Monterey, CA, 93943, USA.

出版信息

Sci Data. 2019 Jul 10;6(1):119. doi: 10.1038/s41597-019-0125-3.

DOI:10.1038/s41597-019-0125-3
PMID:31292448
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6620299/
Abstract

Different from the existing global ocean climatological datasets of isothermal layer (ITL) depth (h), a global ocean synoptic dataset of h along with other parameters has been established from temperature profiles of the National Centers for Environmental Information (NCEI) world ocean database 1961-2017. The exponential leap-forward gradient method was used to identify h and thermocline gradient (G) from each temperature profile measured by expendable bathythermograph (XBT) and conductivity, temperature, depth (CTD) instruments. Due to quality and vertical resolution of the profiling data, the numbers of (G, h) pairs are 446,811 out of 964,942 CTD profiles and 755,086 out of 2,303,433 XBT profiles. With the given h, other parameters such as ITL heat content (H), sea surface temperature (SST), temperature below ITL (T), and quality measures (Q, I) indices are provided. Altogether, the dataset contains 1,201,897 temporally and horizontally varying sets of (G, h, H, SST, T, Q-index, I-index). Note that we added 200° to the longitude. This synoptic dataset is located on the NCEI website for public use.

摘要

与现有的全球海洋等温水层(ITL)深度(h)气候数据集不同,本研究从 1961 年至 2017 年美国国家环境信息中心(NCEI)世界海洋数据库的温盐深仪(CTD)和投弃式温盐深仪(XBT)测量的温度剖面中建立了一个全球海洋天气数据集,其中包含 h 及温跃层梯度(G)等参数。采用指数突跃梯度法从每个温度剖面中识别 h 和温跃层梯度(G)。由于剖面数据的质量和垂直分辨率,在 964942 个 CTD 剖面中有 446811 对(G,h)对,在 2303433 个 XBT 剖面中有 755086 对(G,h)对。给定 h 后,可提供 ITL 热含量(H)、海面温度(SST)、ITL 以下温度(T)以及质量度量(Q、I)指数等其他参数。数据集共包含 1201897 个时变和水平变化的(G,h,H,SST,T,Q 指数,I 指数)数据集。请注意,我们将经度增加了 200°。该天气数据集位于 NCEI 网站上,供公众使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/8a49068452f9/41597_2019_125_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/3429895dd518/41597_2019_125_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/d125dab6bf7b/41597_2019_125_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/5982143965b0/41597_2019_125_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/98c89740b606/41597_2019_125_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/b70af9410c84/41597_2019_125_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/15d263986a8e/41597_2019_125_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/8a49068452f9/41597_2019_125_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/3429895dd518/41597_2019_125_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/d125dab6bf7b/41597_2019_125_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/5982143965b0/41597_2019_125_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/98c89740b606/41597_2019_125_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/b70af9410c84/41597_2019_125_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/15d263986a8e/41597_2019_125_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c225/6620299/8a49068452f9/41597_2019_125_Fig7_HTML.jpg

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