Model derived uncertainties in deep ocean temperature trends between 1990-2010 (dataset)
Model derived uncertainties in deep ocean temperature trends between 1990-2010 (dataset)
复制标题
模型得出 1990-2010 年间深海温度趋势的不确定性（数据集）
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
B. King
中科院分区：
文献类型：
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作者：
F. Garry;E. McDonagh;A. Blaker;C. Roberts;D. Desbruyères;E. Frajka‐Williams;B. King
我们构建了一个新的框架来研究与根据水文剖面估计深海温度变化相关的不确定性和偏差，并在涡流允许的海洋模型中证明了这一框架。由于空间覆盖范围稀疏（一个盆地中的几个部分）、占领频率低（通常相隔5-10年）、感兴趣的时间段与占领跨度之间不匹配以及与一年中某些时间的抽样实际性有关的季节性偏差，观测估计数出现偏差。在1990年至2010年期间，模拟的全球深海海洋偏差很小，尽管在区域上有些偏差（表示为进入4000 - 6000米层的热通量）可高达0.05 W/m²。在这个模型中，由于时间或空间采样的不确定性，进入2000 - 4000米深处的热通量的偏差通常要大得多，在整个海洋中可能超过0.1 W/m²。总体而言，82%的变暖趋势深超过2000米的水文断面式采样模型中捕获。在2000米处，只有一半的全球变暖趋势模型是从观测式采样中获得的，在大西洋、南部和印度洋存在很大的偏差。不同来源的不确定性造成的偏差可能有相反的迹象，在区域和深度上的相对重要性也不同，这表明在未来深海观测设计中减少时间和空间不确定性的重要性。
We construct a novel framework to investigate the uncertainties and biases associated with estimates of deep ocean temperature change from hydrographic sections, and demonstrate this framework in an eddy-permitting ocean model. Biases in estimates from observations arise due to sparse spatial coverage (few sections in a basin), low frequency of occupations (typically 5-10 years apart), mismatches between the time period of interest and span of occupations, and from seasonal biases relating to the practicalities of sampling during certain times of year. Between the years 1990 and 2010, the modeled global abyssal ocean biases are small, although regionally some biases (expressed as a heat flux into the 4000 - 6000 m layer) can be up to 0.05 W/m². In this model, biases in the heat flux into the deep 2000 - 4000 m layer, due to either temporal or spatial sampling uncertainties, are typically much larger and can be over 0.1 W/m² across an ocean. Overall, 82% of the warming trend deeper than 2000 m is captured by hydrographic section-style sampling in the model. At 2000 m, only half the model global warming trend is obtained from observational-style sampling, with large biases in the Atlantic, Southern and Indian Oceans. Biases due to different sources of uncertainty can have opposing signs and differ in relative importance both regionally and with depth, revealing the importance of reducing temporal and spatial uncertainties in future deep ocean observing design.