Estimating Oxygen in the Southern Ocean Using Argo Temperature and Salinity

Giglio D.; Lyubchich V.; Mazloff M. R.

摘要

Abstract > An Argo‐based estimate of oxygen (O <sub>2</sub> ) at 150 m is presented for the Southern Ocean (SO) from temperature (T), salinity (S), and O <sub>2</sub> Argo profiles collected during 2008–2012. The method is based on a supervised machine learning algorithm known as random forest (RF) regression and provides an estimate for O <sub>2</sub> given T, S, location, and time information. The method is validated by attempting to reproduce the Southern Ocean State Estimate (SOSE) O <sub>2</sub> field using synthetic data sampled from SOSE. The RF mapping shows skill in the majority of the domain but is problematic in some of the boundary regions. Maps of O <sub>2</sub> at 150 m derived from observed profiles suggest that SOSE and the World Ocean Atlas 2013 climatology may overestimate annual mean O <sub>2</sub> in the SO, both on a global and basin scale. A large regional bias is found east of Argentina, where high O <sub>2</sub> values in the Argo‐based estimate are confined closer to the coast compared to other products. SOSE may also underestimate the annual cycle of O <sub>2</sub> . Evaluation of the RF‐based method demonstrates its potential to improve understanding of O <sub>2</sub> annual mean fields and variability from sparse O <sub>2</sub> measurements. This implies the algorithm will also be effective for mapping other biogeochemical variables (e.g., nutrients and carbon). Furthermore, our RF evaluation results can be used to inform the design of future enhancements to the current array of O <sub>2</sub> profiling floats. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><Abstract Type =“main”> <标题类型=“main”>抽象</ title> >南部的150米处的氧气（O <sub> 2 </ sub>）的基于ARGO的估计从2008 - 2012年期间收集的温度（T），盐度和O <SUB> 2 </ sub> ARGO型材的海洋（SO）。该方法基于称为随机森林（RF）回归的监督机器学习算法，并提供给定T，S，位置和时间信息的O <sub> 2 </ sub>的估计。通过尝试使用从Sose采样的合成数据再现南洋估计（SOSE）O <SUB> 2 <sub> 2 </ sub>字段来验证该方法。 RF映射显示了大多数域的技能，但在一些边界区域中存在问题。 O <SUB> 2 </ sub>的地图衍生自观察到的型材的150米，表明SOSE和世界海洋地图集2013年气候学可能会高估每年平均值O <SUB> 2 </ SUB>在全球和盆地比例。与其他产品相比，阿根廷以东发现了一个大型区域偏见，其中基于Argo的估计中的高O <sub> 2 </ sub>值局限于海岸。 SOSE也可能低估O <SUB> 2 </ sub>的年度周期。基于RF的方法的评估证明了其提高对O <SUB> 2 </ SUB>年平均字段和可变性的潜力，从稀疏O <sub> 2 </ sub>测量。这意味着算法也将有效地映射其他生物地造影变量（例如，营养物质和碳）。此外，我们的射频评估结果可用于向未来的增强功能通知对O <SUB> 2 </ sub>分析浮点数的当前阵列的设计。 </ p> </ abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-34643/'>《Journal of Geophysical Research, C. Oceans: JGR》</a> <b style="margin: 0 2px;">|</b><span>2018年第6期</span><b style="margin: 0 2px;">|</b><span>共18页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Giglio D.&option=202" target="_blank" rel="nofollow">Giglio D.;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Lyubchich V.&option=202" target="_blank" rel="nofollow">Lyubchich V.;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Mazloff M. R.&option=202" target="_blank" rel="nofollow">Mazloff M. R.;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Scripps Institution of OceanographyUniversity of California San DiegoLa Jolla CA USA;</p> <p>Chesapeake Biological LaboratoryUniversity of Maryland Center for Environmental ScienceSolomons MD USA;</p> <p>Scripps Institution of OceanographyUniversity of California San DiegoLa Jolla CA USA;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/163.html" title="地球物理学">地球物理学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=oxygen&option=203" rel="nofollow">oxygen;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Argo and BGC‐Argo&option=203" rel="nofollow">Argo and BGC‐Argo;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Southern Ocean&option=203" rel="nofollow">Southern Ocean;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Southern Ocean State Estimate (SOSE)&option=203" rel="nofollow">Southern Ocean State Estimate (SOSE);</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=mapping methods&option=203" rel="nofollow">mapping methods;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=machine learning&option=203" rel="nofollow">machine learning;</a> </p> <div class="translation"> 机译：氧气;ARGO和BGC-ARGO;南海;南海州估计（SOSE）;映射方法;机器学习; </div> </li> </ul> </div> </div> <div class="literature cardcommon"> <div class="similarity "> <h3 class="all_title" id="enpatent66">相似文献</h3> <div class="similaritytab clearfix"> <ul> <li class="active" >外文文献</li> <li >中文文献</li> <li >专利</li> </ul> </div> <div class="similarity_details"> <ul > <li> <div> <b>1. </b><a class="enjiyixqcontent" href="/journal-foreign-detail/0704025580713.html">Estimating Oxygen in the Southern Ocean Using Argo Temperature and Salinity</a> <b>[J]</b> . <span> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Giglio D.&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Giglio D.,</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Lyubchich V.&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Lyubchich V.,</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Mazloff M. 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