Nested cross-validation Gaussian process to model dimethylsulfide mesoscale variations in warm oligotrophic Mediterranean seawater

IF 8.5 1区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Karam Mansour, Stefano Decesari, Marco Paglione, Silvia Becagli, Matteo Rinaldi
{"title":"Nested cross-validation Gaussian process to model dimethylsulfide mesoscale variations in warm oligotrophic Mediterranean seawater","authors":"Karam Mansour, Stefano Decesari, Marco Paglione, Silvia Becagli, Matteo Rinaldi","doi":"10.1038/s41612-024-00830-y","DOIUrl":null,"url":null,"abstract":"The study proposes an approach to elucidate spatiotemporal mesoscale variations of seawater Dimethylsulfide (DMS) concentrations, the largest natural source of atmospheric sulfur aerosol, based on the Gaussian Process Regression (GPR) machine learning model. Presently, the GPR was trained and evaluated by nested cross-validation across the warm-oligotrophic Mediterranean Sea, a climate hot spot region, leveraging the high-resolution satellite measurements and Mediterranean physical reanalysis together with in-situ DMS observations. The end product is daily gridded fields with a spatial resolution of 0.083° × 0.083° (~9 km) that spans 23 years (1998–2020). Extensive observations of atmospheric methanesulfonic acid (MSA), a typical biogenic secondary aerosol component from DMS oxidation, are consistent with the parameterized high-resolution estimates of sea-to-air DMS flux (FDMS). This represents substantial progress over existing coarse-resolution DMS global maps which do not accurately depict the seasonal patterns of MSA in the Mediterranean atmospheric boundary layer.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5000,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00830-y.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://www.nature.com/articles/s41612-024-00830-y","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The study proposes an approach to elucidate spatiotemporal mesoscale variations of seawater Dimethylsulfide (DMS) concentrations, the largest natural source of atmospheric sulfur aerosol, based on the Gaussian Process Regression (GPR) machine learning model. Presently, the GPR was trained and evaluated by nested cross-validation across the warm-oligotrophic Mediterranean Sea, a climate hot spot region, leveraging the high-resolution satellite measurements and Mediterranean physical reanalysis together with in-situ DMS observations. The end product is daily gridded fields with a spatial resolution of 0.083° × 0.083° (~9 km) that spans 23 years (1998–2020). Extensive observations of atmospheric methanesulfonic acid (MSA), a typical biogenic secondary aerosol component from DMS oxidation, are consistent with the parameterized high-resolution estimates of sea-to-air DMS flux (FDMS). This represents substantial progress over existing coarse-resolution DMS global maps which do not accurately depict the seasonal patterns of MSA in the Mediterranean atmospheric boundary layer.

Abstract Image

Abstract Image

用嵌套交叉验证高斯过程模拟地中海暖寡营养海水中的二甲基硫醚中尺度变化
该研究提出了一种基于高斯过程回归(GPR)机器学习模型的方法,用于阐明海水二甲基硫化物(DMS)浓度的时空中尺度变化,DMS是大气硫气溶胶的最大天然来源。目前,利用高分辨率卫星测量和地中海物理再分析以及现场二甲基硫化物观测数据,通过嵌套交叉验证,对气候热点地区地中海的暖-异养地中海进行了 GPR 训练和评估。最终结果是空间分辨率为 0.083°×0.083°(约 9 千米)的日网格场,时间跨度为 23 年(1998-2020 年)。大气中的甲磺酸(MSA)是二甲基亚砜氧化作用产生的典型生物次生气溶胶成分,其广泛观测结果与海气二甲基亚砜通量(FDMS)的参数化高分辨率估算结果一致。与现有的粗分辨率二甲基亚砜全球地图相比,这是一项重大进步,因为现有的粗分辨率二甲基亚砜全球地图无法准确描绘地中海大气边界层中二甲基亚砜的季节性模式。
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
npj Climate and Atmospheric Science
npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science
CiteScore
8.80
自引率
3.30%
发文量
87
审稿时长
21 weeks
期刊介绍: npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.
×
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