A high-resolution air-sea synoptic observation dataset from drifting buoys in the Bay of Bengal

IF 13.6 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Earth System Science Data Pub Date : 2026-09-03 DOI:10.5194/essd-18-6411-2026

Wei Huang,Guihua Wang,Changlin Chen,Gengxin Chen,Weiqiang Wang

{"title":"A high-resolution air-sea synoptic observation dataset from drifting buoys in the Bay of Bengal","authors":"Wei Huang,Guihua Wang,Changlin Chen,Gengxin Chen,Weiqiang Wang","doi":"10.5194/essd-18-6411-2026","DOIUrl":null,"url":null,"abstract":"Abstract. Mass and heat exchanges at the air-sea interface fundamentally drive global weather and climate systems. However, acquiring long-term, high-frequency, synchronous in-situ observations of both atmospheric and oceanic variables remain highly challenging, especially during extreme weather. This paper presents a high-resolution dataset from five air-sea drifting buoys deployed in the Bay of Bengal (BoB) in 2020 and 2022. These buoys captured precise, synchronous measurements of key meteorological parameters (air temperature, sea-level pressure, wind speed and direction, and relative humidity) alongside sea surface temperature. The dataset is typically sampled hourly; however, the sampling was increased to 5 min intervals during tropical cyclones Nivar, Burevi, Four and Asani. This high-frequency dataset offers invaluable in-situ records for studying diurnal variations and fine-scale processes in the BoB. Furthermore, it provides critical observational data to advance our understanding of air-sea coupling, validate high-frequency satellite products, and improve parameterizations in regional numerical weather prediction models under extreme conditions. The dataset is freely available at https://doi.org/10.5281/zenodo.21294873 (Huang et al., 2026).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"138 1","pages":"6411-6419"},"PeriodicalIF":13.6000,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth System Science Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/essd-18-6411-2026","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Abstract. Mass and heat exchanges at the air-sea interface fundamentally drive global weather and climate systems. However, acquiring long-term, high-frequency, synchronous in-situ observations of both atmospheric and oceanic variables remain highly challenging, especially during extreme weather. This paper presents a high-resolution dataset from five air-sea drifting buoys deployed in the Bay of Bengal (BoB) in 2020 and 2022. These buoys captured precise, synchronous measurements of key meteorological parameters (air temperature, sea-level pressure, wind speed and direction, and relative humidity) alongside sea surface temperature. The dataset is typically sampled hourly; however, the sampling was increased to 5 min intervals during tropical cyclones Nivar, Burevi, Four and Asani. This high-frequency dataset offers invaluable in-situ records for studying diurnal variations and fine-scale processes in the BoB. Furthermore, it provides critical observational data to advance our understanding of air-sea coupling, validate high-frequency satellite products, and improve parameterizations in regional numerical weather prediction models under extreme conditions. The dataset is freely available at https://doi.org/10.5281/zenodo.21294873 (Huang et al., 2026).

查看原文本刊更多论文

孟加拉湾漂流浮标的高分辨率海气天气观测数据集

摘要。海气界面的质量和热量交换从根本上驱动着全球天气和气候系统。然而，获取大气和海洋变量的长期、高频、同步原位观测仍然极具挑战性，特别是在极端天气期间。本文介绍了2020年和2022年部署在孟加拉湾（BoB）的五个气海漂流浮标的高分辨率数据集。这些浮标捕获了精确的、同步的关键气象参数（气温、海平面压力、风速和风向、相对湿度）以及海面温度。数据集通常每小时采样一次；然而，在热带气旋Nivar、Burevi、Four和Asani期间，采样时间增加到每隔5分钟。该高频数据集为研究北冰洋的日变化和精细尺度过程提供了宝贵的原位记录。此外，它还提供了重要的观测数据，以促进我们对海气耦合的理解，验证高频卫星产品，并改进极端条件下区域数值天气预报模式的参数化。该数据集可在https://doi.org/10.5281/zenodo.21294873免费获取（Huang et al., 2026）。

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

Earth System Science Data GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES

CiteScore

18.00

自引率

5.30%

发文量

231

审稿时长

35 weeks

期刊介绍： Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.