Tropical Air-Sea Interactions and Their Impact on East Asian Anomalous Climate

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 2618

Special Issue Editors

College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
Interests: multi-satellite altimeter mapping; ocean dynamic topography; typhoon-ocean interaction; typhoon numerical simulation
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Guest Editor
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: air–sea interaction; climate dynamics; extreme weather and climate events
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ocean is a crucial component of the climate system, covering approximately 71% of the Earth's surface. Air-sea interactions significantly impact the climate system, and the influence of tropical air-sea interactions on anomalous climate has garnered increasing attention. East Asia is a densely populated region heavily influenced by the East Asian monsoon. Tropical air-sea interactions, such as ENSO, can affect East Asian summer anomalous climate by modulating the East Asian summer monsoon. For example, the extreme El Niño event of 1997/98 significantly contributed to the extreme summer precipitation in the middle and lower reaches of the Yangtze River in the summer of 1998. Similarly, the extreme positive IOD event in the fall of 2019 is closely linked to the violent Meiyu in the middle and lower reaches of the Yangtze River during the summer of 2020. Anomalous sea surface temperatures in the tropical Atlantic can also influence East Asian summer anomalous climate by modulating the East Asian summer monsoon through air-sea interactions.

Against the background of global warming, sea surface height (SSH) is the most intuitive response to global climate change. In atmosphere-ocean interactions, changes in ocean heat capacity and the thermodynamic structure of the atmospheric boundary layer are closely related to SSH, which greatly impacts human production and life. At present, the most effective tool for monitoring changes in SSH is the satellite altimeter, which can effectively monitor the multi-scale structural characteristics of the oceans using the altimeter carried by the satellite and then using mapping methods to obtain SSH on a regular grid from the data along the orbit. The recently launched Surface Water and Ocean Topography (SWOT) satellite, is equipped with a cutting-edge Ka-band radar characterized by reduced noise levels, expansive swath width, and heightened resolution. It has globally undergone extensive in-situ observation calibration and validation and several exploratory applications in coastal tide research, data assimilation, etc. It shows great promise for a wide range of applications in the fields of physical oceanography, biogeophysical interaction, atmospheric dynamics, etc.

This special issue will focus on the occurrence, development patterns, and formation mechanisms of tropical air-sea interaction phenomena, as well as their impacts on East Asian anomalous climate and oceanic variables. The aim is to provide a scientific basis and clues for a deeper understanding of anomalous climate in the East Asian region and for disaster prevention and mitigation efforts. This Special Issue invites submissions of original research, review articles, and perspectives on the following topics:

  1. Spatiotemporal evolution patterns and formation mechanisms of air-sea interactions in the three tropical oceans;
  2. Mechanisms of the impact of air-sea interactions on East Asian climate anomalies;
  3. Statistical analysis and cause analysis of extreme climate events in East Asia;
  4. Research on the mechanism of air-sea interactions in East Asian oceanic variables (e.g., ocean mesoscale eddies and sea surface height).
  5. Analysis of the structure and formation mechanism of ocean mesoscale eddiesand assimilation methods for SSH remote sensing data;

Dr. Lei Liu
Dr. Dachao Jin
Guest Editors

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Keywords

  • air-sea interactions
  • east Asian anomalous climate
  • sea surface height
  • ocean mesoscale eddies

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Published Papers (3 papers)

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Research

12 pages, 2708 KiB  
Article
The Roles of the Eastern Atlantic Niño and Central Atlantic Niño in ENSO Prediction
by Yuzhi Gan, Xingchen Shen, Yishuai Jin, Zhengxiang Rao, Yiqun Pang and Shouyou Huang
Atmosphere 2024, 15(12), 1433; https://doi.org/10.3390/atmos15121433 - 29 Nov 2024
Viewed by 588
Abstract
Recent studies have shown that there are two types of Niño events in the Tropical Atlantic, namely the Eastern Atlantic (EA) Niño and Central Atlantic (CA) Niño modes. However, it remains unknown whether these two types of Niño modes still impact El Niño–Southern [...] Read more.
Recent studies have shown that there are two types of Niño events in the Tropical Atlantic, namely the Eastern Atlantic (EA) Niño and Central Atlantic (CA) Niño modes. However, it remains unknown whether these two types of Niño modes still impact El Niño–Southern Oscillation (ENSO) prediction. This paper investigates the impacts of the EA and CA Niño modes on ENSO predictability with an empirical dynamical model: the Linear Inverse Model (LIM). After selectively including in or excluding from the LIM the EA and CA modes of the Tropical Atlantic, respectively, we discover that the EA mode has a greater significance in ENSO prediction compared to the CA mode. The evolution of the EA and CA mode optimum initial structures also confirms the impact of the EA mode on the Tropical Pacific. Further study shows that the EA mode can improve the Eastern Pacific (EP)-ENSO and Central Pacific (CP)-ENSO predictions, while the CA mode plays a less important role. Despite the significant influence of the EA mode, the CA mode has become increasingly important since the 2000s and the EA mode has been weakened in recent years. Therefore, the role of the CA mode in ENSO prediction after 2000 should be considered in the future. Full article
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15 pages, 7289 KiB  
Article
The Different Effects of Two Types of El Niño on Eastern China’s Spring Precipitation During the Decaying Stages
by Dezhi Zhang, Chujie Gao, Zhichao Yang, Zhi Yuan, Xuanke Wang, Bei Xu and Haozhong Qian
Atmosphere 2024, 15(11), 1331; https://doi.org/10.3390/atmos15111331 - 5 Nov 2024
Cited by 2 | Viewed by 879
Abstract
El Niño is one of the most significant global climatic phenomena affecting the East Asian atmospheric circulation and climate. This study uses multi-source datasets, including observations and analyses, and statistical methods to investigate the variations and potential causes of boreal spring precipitation anomalies [...] Read more.
El Niño is one of the most significant global climatic phenomena affecting the East Asian atmospheric circulation and climate. This study uses multi-source datasets, including observations and analyses, and statistical methods to investigate the variations and potential causes of boreal spring precipitation anomalies in eastern China under different El Niño sea surface temperature conditions, namely, the Eastern Pacific and Central Pacific (EP and CP) El Niño cases. The findings reveal that, particularly along the Yangtze–Huaihe valley, spring precipitation markedly increases in most regions of eastern China during the EP El Niño decaying stages. Conversely, during the CP El Niño decaying stages, precipitation anomalies are weak, with occurrences of weak negative anomalies in the same regions. Further analyses reveal that during the decaying spring of different El Niño cases, differences in the location and strength of the Northwest Pacific (NWP) abnormal anticyclone, which is associated with the central–eastern Pacific warm sea surface temperature anomaly (SSTA), result in distinct anomalous precipitation responses in eastern China. The SSTA center of the EP El Niño is more easterly and stronger. In the meantime, NWP abnormal anticyclones are more easterly and have a broader range, facilitating water vapor transport over eastern China. By contrast, the CP El Niño SSTA center is westward and relatively weaker, leading to a relatively weak, westward, and narrower anomalous NWP anticyclone that causes less significant water vapor transport anomalies in eastern China. This paper highlights the diverse impacts of El Niño diversity on regional atmospheric circulation and precipitation, providing valuable scientific references for studying regional climate change in East Asia. Full article
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23 pages, 7991 KiB  
Article
Estimating Subsurface Thermohaline Structure in the Tropical Western Pacific Using DO-ResNet Model
by Xianmei Zhou, Shanliang Zhu, Wentao Jia and Hengkai Yao
Atmosphere 2024, 15(9), 1043; https://doi.org/10.3390/atmos15091043 - 29 Aug 2024
Viewed by 688
Abstract
Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and the El Niño phenomenon. This paper proposes an improved double-output residual neural network (DO-ResNet) model to concurrently estimate the subsurface temperature (ST) and subsurface salinity (SS) in [...] Read more.
Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and the El Niño phenomenon. This paper proposes an improved double-output residual neural network (DO-ResNet) model to concurrently estimate the subsurface temperature (ST) and subsurface salinity (SS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly (SSHA), sea surface wind (SSW), and geographical information (including longitude and latitude). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE), and coefficient of determination (R2) were employed to evaluate the model’s performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R2 values for estimating ST (SS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model’s accuracy by comparing its estimations of ST and SS across different depths with Argo data, demonstrating the model’s ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model demonstrates strong adaptability to seasonal variations. In conclusion, this research introduces a novel artificial intelligence technique for estimating ST and SS in the tropical Western Pacific Ocean. Full article
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