| 利用全球温盐观测剖面计划资料估算太平洋上层跨等密度面混合 |
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| 引用本文： | 邓增安,韦广昊,于婷,魏红宇,康林冲,韩璐遥.利用全球温盐观测剖面计划资料估算太平洋上层跨等密度面混合[J].海洋学报(英文版),2016,35(1):46-52. |
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| 作者姓名： | 邓增安 韦广昊 于婷 魏红宇 康林冲 韩璐遥 |
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| 作者单位： | 天津大学, 海洋科学与技术学院;国家海洋信息中心,国家海洋信息中心,国家海洋信息中心,国家海洋信息中心,国家海洋信息中心,国家海洋信息中心 |
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| 摘 要： | 基于全球多年来积累的大量温盐观测剖面计划资料,利用精细尺度参数化方案估算了太平洋上层600米区域内的跨等密度面混合系数。结果表明,在不同季节跨等密度面混合系数的整体分布类似,但是细节上存在很大的不同。跨等密度面混合系数的加强与底部摩擦、海表面近惯性能量输入、赤道效应等因素密切相关。由于粗糙的地形,混合在东北太平洋门多西诺断裂带附近存在明显加强。同时,在南大洋西风带区域,由于大风引起的近惯性能量输入也导致了混合的强化。 与前人的研究结果相比,本文的估算具有更好的空间覆盖率以及更高的分辨率,更重要的是我们的结果体现了季节性变化。由于我们给出的是网格化产品,非常适合在数值模式中的应用。
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| 关 键 词： | 跨等密度面混合 全球温盐观测剖面计划 精细尺度参数化 太平洋 |
| 收稿时间： | 2014/10/22 0:00:00 |
| 修稿时间： | 3/9/2015 12:00:00 AM |
The diapycnal mixing in the upper Pacific estimated from GTSPP observations |
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| DENG Zeng''an,WEI Guanghao,YU Ting,WEI Hongyu,KANG Linchong and HAN Luyao.The diapycnal mixing in the upper Pacific estimated from GTSPP observations[J].Acta Oceanologica Sinica,2016,35(1):46-52. |
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| Authors: | DENG Zeng'an WEI Guanghao YU Ting WEI Hongyu KANG Linchong and HAN Luyao |
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| Institution: | 1.School of Marine Science and Technology, Tianjin University, Tianjin 300172, China;National Marine Data and Information Service, Tianjin 300171, China2.National Marine Data and Information Service, Tianjin 300171, China |
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| Abstract: | Diapycnal mixing (DM) in the upper 600 m of the Pacific Ocean was estimated based on the huge amount of the observations from Global Temperature-Salinity Profile Programme (GTSPP), using the strain version of the finescale parameterization. It is found that DM in each season exhibits similar distribution pattern, but differs in details. The intensification of DM is related to bottom roughness, surface near-inertial energy, and proximity to the equator. The intensified DM caused by rough topography shows in the profiles near the Mendocino fracture zone in the northeast Pacific, and the heightened DM caused by wind-generated near-inertial energy appears in the westerly region of the Southern Ocean. As compared to previous estimates, the DM estimate in this work has better spatial coverage and finer resolution, and more importantly it contains the seasonal variability. Furthermore, the resulting DM dataset is gridded, rendering it suitable for modeling applications. |
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| Keywords: | diapycnal mixing GTSPP fine-scale parameterization Pacific |
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