Variability in efficiency of particulate organic carbon export: A model study
Variability in efficiency of particulate organic carbon export: A model study
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DOI：
10.1002/2014gb004965
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发表时间：
2015-01
影响因子：
5.2
通讯作者：
S. Henson;A. Yool;R. Sanders
中科院分区：
文献类型：
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作者：
S. Henson;A. Yool;R. Sanders
有机碳从海洋表层流向中层深度是全球碳循环的一个关键组成部分，并最终来自浮游植物的初级生产力。只有一小部分由PP产生的有机碳从上层海洋输出，称为输出效率（本文中的e-比率）。有限的观测的e比率，因此有相当大的兴趣，使用遥感参数，如海面温度外推当地估计全球年度输出通量。目前，以这种方式得出的出口估计数之间存在很大差异;一个可能的解释是观察中的空间或时间抽样偏差。在这里，我们使用高分辨率的全球地球化学模型来研究e比率的空间和季节变化的全球模式以及随后对出口估计的影响。这里使用的模型将输出表示为单独的缓慢和快速下沉的碎屑材料，其再矿化分别取决于温度和压载矿物的函数。我们发现，温度和缓慢下沉粒子携带的输出分数都是确定e-ratio的因素，这表明目前只考虑温度的e-ratio经验算法过于简单。我们量化了PP和出口之间的时间滞后，这在PP变化性强的地区是最大的，在这些地区，季节性解耦可能导致较大的e比率变化。从瞬时测量的e比率外推全球出口估计值受到季节性变化的强烈影响，可能导致估计出口的误差高达± 60%。
The flux of organic carbon from the surface ocean to mesopelagic depths is a key component of the global carbon cycle and is ultimately derived from primary production (PP) by phytoplankton. Only a small fraction of organic carbon produced by PP is exported from the upper ocean, referred to as the export efficiency (herein e‐ratio). Limited observations of the e‐ratio are available, and there is thus considerable interest in using remotely sensed parameters such as sea surface temperature to extrapolate local estimates to global annual export flux. Currently, there are large discrepancies between export estimates derived in this way; one possible explanation is spatial or temporal sampling bias in the observations. Here we examine global patterns in the spatial and seasonal variability in e‐ratio and the subsequent effect on export estimates using a high‐resolution global biogeochemical model. The model used here represents export as separate slow‐ and fast‐sinking detrital material whose remineralization is respectively temperature dependent and a function of ballasting minerals. We find that both temperature and the fraction of export carried by slow‐sinking particles are factors in determining e‐ratio, suggesting that current empirical algorithms for e‐ratio that only consider temperature are overly simple. We quantify the temporal lag between PP and export, which is greatest in regions of strong variability in PP where seasonal decoupling can result in large e‐ratio variability. Extrapolating global export estimates from instantaneous measurements of e‐ratio is strongly affected by seasonal variability and can result in errors in estimated export of up to ±60%.