Atmospheric Water Vapor Transport between Ocean and Land under Climate Warming

Author:

Wang Jialin123,Pan Feifei4,An Pingli2,Han Guolin35,Jiang Kang13,Song Yu13,Huang Na13,Zhang Ziyuan13,Ma Shangqian13,Chen Xiao13,Pan Zhihua13

Affiliation:

1. a College of Resources and Environmental Sciences, China Agricultural University, Beijing, China

2. b College of Land Science and Technology, China Agricultural University, Beijing, China

3. c CMA-CAU Joint Laboratory of Agriculture Addressing Climate Change, Beijing, China

4. d Department of Geography and the Environment, University of North Texas, Denton, Texas

5. e China Meteorological Administration Training Center, Beijing, China

Abstract

Abstract Global warming intensifies atmospheric water vapor transport between ocean and land, which increases the likelihood of extreme precipitation and floods. However, accurate estimations of water vapor exchange between ocean and land are difficult due to the lack of available data and effective methods. This study developed a novel eight-direction-vector decomposition algorithm for calculating water vapor flux between ocean and land based on the ERA5 dataset, and the results showed that global water vapor exchange between ocean and land had significantly increased in the past 40 years, except for Antarctica. During 1980–2018, the average annual net water vapor inflow from ocean to land (Qnet) was 44.68 × 1015 kg yr−1, and Qnet increased at a rate of 1.48 × 1015 kg yr−1 decade−1. The intensified atmospheric water vapor exchange between ocean and land was directly caused by the increase of atmospheric water vapor content, which largely depended on the rising air temperature, and it was found that water vapor flux between ocean and land increased by over 8% K−1 with the increasing air temperature at the global average. This study also identified El Niño–Southern Oscillation (ENSO) as an important contributor to the global ocean–land water vapor exchange anomalies. A strong El Niño event (MEI = 1) can result in a 1.36 × 1015 kg yr−1 (3.03%) decrease in Qnet, and a strong La Niña event (MEI = −1) can increase Qnet by 1.38 × 1015 kg yr−1 (3.09%). The eight-direction-vector decomposition algorithm was effective in ocean–land water vapor flux estimations at different spatial and temporal scales, which could provide great insights into the mechanisms of extreme precipitation events. Significance Statement This study developed a novel approach on water vapor flux estimation (i.e., the eight-direction-vector decomposition algorithm) and achieved a high-temporal–spatial-resolution estimation of water vapor flux between ocean and land. It was found that water vapor flux between ocean and land was intensified by increasing air temperature at a rate of 8% K−1, and El Niño yielded an anomaly low net water vapor input from ocean to land at the global scale. The algorithm developed in this study can be used for estimating water vapor fluxes at different spatial and temporal scales, which is crucial for evaluating the role of water vapor flux on formations for extreme weather (e.g., torrential rainstorms and heat waves) and climatic extremes (e.g., droughts and floods).

Funder

China Scholarship Council

National Key R&D program of China

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference75 articles.

1. Atmospheric warming and the amplification of precipitation extremes;Allan, R. P.,2008

2. Future increases in extreme precipitation exceed observed scaling rates;Bao, J.,2017

3. Water vapor tracers as diagnostics of the regional hydrologic cycle;Bosilovich, M. G.,2002

4. Estimation of continental precipitation recycling;Brubaker, K. L.,1993

5. Atmospheric water vapor transport and continental hydrology over the Americas;Brubaker, K. L.,1994

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3