Deciphering the variability in air-sea gas transfer due to sea state and wind history

Mingxi Yang, David Moffat, Yuanxu Dong, Jean-Raymond Bidlot
{"title":"Deciphering the variability in air-sea gas transfer due to sea state and wind history","authors":"Mingxi Yang, David Moffat, Yuanxu Dong, Jean-Raymond Bidlot","doi":"10.1093/pnasnexus/pgae389","DOIUrl":null,"url":null,"abstract":"Understanding processes driving air-sea gas transfer and being able to model both its mean and variability are critical for studies of climate and carbon cycle. The air-sea gas transfer velocity (K660) is almost universally parameterized as a function of wind speed in large scale models – an oversimplification that buries the mechanisms controlling K660 and neglects much natural variability. Sea state has long been speculated to affect gas transfer, but consistent relationships from in situ observations have been elusive. Here, applying a Machine Learning technique to an updated compilation of shipboard direct observations of the CO2 transfer velocity (KCO2,660), we show that the inclusion of significant wave height improves the model simulation of KCO2,660, while parameters such as wave age, wave steepness, and swell-wind directional difference have little influence on KCO2,660. Wind history is found to be important, as in high seas KCO2,660 during periods of falling winds exceed periods of rising winds by ∼20% in the mean. This hysteresis in KCO2,660 is consistent with the development of waves and increase in whitecap coverage as the seas mature. A similar hysteresis is absent from the transfer of a more soluble gas, confirming that the sea state dependence in KCO2,660 is primarily due to bubble-mediated gas transfer upon wave breaking. We propose a new parameterization of KCO2,660 as a function of wind stress and significant wave height, which resemble observed KCO2,660 both in the mean and on short timescales.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PNAS Nexus","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/pnasnexus/pgae389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Understanding processes driving air-sea gas transfer and being able to model both its mean and variability are critical for studies of climate and carbon cycle. The air-sea gas transfer velocity (K660) is almost universally parameterized as a function of wind speed in large scale models – an oversimplification that buries the mechanisms controlling K660 and neglects much natural variability. Sea state has long been speculated to affect gas transfer, but consistent relationships from in situ observations have been elusive. Here, applying a Machine Learning technique to an updated compilation of shipboard direct observations of the CO2 transfer velocity (KCO2,660), we show that the inclusion of significant wave height improves the model simulation of KCO2,660, while parameters such as wave age, wave steepness, and swell-wind directional difference have little influence on KCO2,660. Wind history is found to be important, as in high seas KCO2,660 during periods of falling winds exceed periods of rising winds by ∼20% in the mean. This hysteresis in KCO2,660 is consistent with the development of waves and increase in whitecap coverage as the seas mature. A similar hysteresis is absent from the transfer of a more soluble gas, confirming that the sea state dependence in KCO2,660 is primarily due to bubble-mediated gas transfer upon wave breaking. We propose a new parameterization of KCO2,660 as a function of wind stress and significant wave height, which resemble observed KCO2,660 both in the mean and on short timescales.
解读海况和风力历史导致的海气传输变化
了解驱动海气传输的过程并能够模拟其平均值和变异性对气候和碳循环研究至关重要。在大尺度模式中,海气传输速度(K660)几乎普遍被参数化为风速的函数--这种过度简化的做法掩盖了控制 K660 的机制,并忽略了许多自然变化。长期以来,人们一直推测海况会影响气体传输,但从现场观测到的一致关系一直难以捉摸。在此,我们将机器学习技术应用于二氧化碳传输速度(KCO2,660)的最新船载直接观测资料汇编,结果表明,加入显著波高可改善模型对 KCO2,660 的模拟,而波龄、波陡和膨胀风向差等参数对 KCO2,660 的影响很小。在公海,风速下降时的 KCO2,660 平均值比风速上升时高 20%。KCO2,660 的这种滞后现象与波浪的发展和海域成熟时白帽覆盖率的增加是一致的。可溶性更强的气体的转移不存在类似的滞后现象,这证实了 KCO2,660 的海况依赖性主要是由于破浪时气泡介导的气体转移造成的。我们提出了一种新的 KCO2,660 参数,它是风压和显著波高的函数,与观测到的 KCO2,660 平均值和短时标相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信