Air-Sea Interactions: Recent Trends, Current Progress and Future Directions

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 4167

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Department of Agricultural Engineering, Federal University of Viçosa, Viçosa 36570-900, MG, Brazil
Interests: ENSO; climate extremes; climate changes; oceanic heat waves
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Special Issue Information

Dear Colleagues,

Air–sea interactions refer to the complex and dynamic interplay between the Earth's atmosphere and its oceans. These interactions are fundamental to understanding and predicting weather, climate, and various environmental processes. They play a crucial role in shaping global and regional climate patterns, ocean currents, weather systems, and extreme events. This Special Issue focuses on fostering a better understanding of how the fluctuations in air–sea interactions in recent decades have induced modifications in global and regional precipitation, evaporation, oceanic surface processes such as upwelling and downwelling, cyclone frequency, and climate teleconnections. It is particularly important to investigate how the impact of inter-annual changes in air–sea interactions leads to modifications in water balance and heat stress. Finally, it is encouraged to submit studies on marine ecosystems and biodiversity, heat waves and costal and human impact.

Prof. Dr. Flávio Justino
Guest Editor

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Keywords

  • climate change
  • oceanic modes
  • sea ice
  • monsoons
  • paleoceanography

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Published Papers (3 papers)

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Research

19 pages, 4401 KiB  
Article
Spatio-Temporal Variability in CO2 Fluxes in the Atlantic Sector of the Southern Ocean
by Gabrielle Tavares de Carvalho, Luciano Ponzi Pezzi, Nathalie Lefèvre, Celina Cândida Ferreira Rodrigues, Marcelo Freitas Santini and Carlos Mejia
Atmosphere 2025, 16(3), 319; https://doi.org/10.3390/atmos16030319 - 10 Mar 2025
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Abstract
The Southern Ocean (SO) plays a fundamental role in the planet’s climate system, due to its ability to absorb and redistribute heat and CO2 (an important greenhouse gas). In addition, the SO connects three large oceanic basins the Pacific, the Atlantic, and [...] Read more.
The Southern Ocean (SO) plays a fundamental role in the planet’s climate system, due to its ability to absorb and redistribute heat and CO2 (an important greenhouse gas). In addition, the SO connects three large oceanic basins the Pacific, the Atlantic, and the Indian Oceans, and it has an important role in the nutrient distribution in these oceans. However, the SO is poorly sampled, with most measurements made in austral spring and summer. The variability in the air–sea CO2 flux is estimated, as well as the role of atmospheric and oceanic variables in this variability. The CO2 fluxes are calculated using the bulk parameterization method, in the Atlantic sector of the Southern Ocean, from 2003 to 2022, using in situ measurements, satellites, and a reanalysis data set. A neural network model is built to produce maps of the partial pressure of CO2 in seawater (pCO2sea). The CO2 flux varies from −0.05 to 0.05 gC m−2 month−1. The Atlantic sector of the SO is a sink of CO2 in summer and spring and becomes a source in austral winter and autumn. The CO2 absorption intensifies from 2003 to 2022 by 7.6 mmol m−2 month−1, due to stronger westerly winds, related to the trend in the positive phase of the Antarctic Oscillation and the extreme El Niño Southern Ocean (ENSO) events (e.g., El Niño and La Niña). Full article
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23 pages, 27902 KiB  
Article
Spatio-Temporal Characteristics of Climate Extremes in Sub-Saharan Africa and Potential Impact of Oceanic Teleconnections
by Lormido Ernesto Zita, Flávio Justino, Carlos Gurjão, James Adamu and Manuel Talacuece
Atmosphere 2025, 16(1), 86; https://doi.org/10.3390/atmos16010086 - 15 Jan 2025
Viewed by 1796
Abstract
Sub-Saharan Africa (SSA) is a region vulnerable to extreme weather events due to its low level of adaptive capacity. In recent decades, SSA has been punctuated by more intense climatic phenomena that severely affect its population. Therefore, this study evaluates the performance of [...] Read more.
Sub-Saharan Africa (SSA) is a region vulnerable to extreme weather events due to its low level of adaptive capacity. In recent decades, SSA has been punctuated by more intense climatic phenomena that severely affect its population. Therefore, this study evaluates the performance of the ERA5 and CHIRPS datasets, and the spatio-temporal evolution of extreme weather indices and their potential relationship/response to climate variability modes in the Pacific, Indian, and Atlantic oceans, namely, the El Niño−Southern Oscillation, Indian Ocean Dipole, and Tropical Atlantic Variability (ENSO, IOD, and TAV). The CHIRPS dataset showed strong positive correlations with CPC in spatial patterns and similarity in simulating interannual variability and in almost all seasons. Based on daily CHIRPS and CPC data, nine extreme indices were evaluated focusing on regional trends and change detection, and the maximum lag correlation method was applied to investigate fluctuations caused by climate variability modes. The results revealed a significant decrease in total precipitation (PRCPTOT) in north−central SSA, accompanied by a reduction in Consecutive Wet Days (CWDs) and maximum 5-day precipitation indices (RX5DAYS). At the same time, there was an increase in Consecutive Dry Days (CDDs) and maximum rainfall in 1 day (RX1DAY). With regard to temperatures, absolute minimums and maximums (TNn and TXn) showed a tendency to increase in the center−north and decrease in the south of the SSA, while daily maximums and minimums (TXx and TNx) showed the opposite pattern. The IOD, TAV, and ENSO modes of climate variability influence temperature and precipitation variations in the SSA, with distinct regional responses and lags between the basins. Full article
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23 pages, 13662 KiB  
Article
High Water Level Forecast Under the Effect of the Northeast Monsoon During Spring Tides
by Yat-Chun Wong, Hiu-Fai Law, Ching-Chi Lam and Pak-Wai Chan
Atmosphere 2024, 15(11), 1321; https://doi.org/10.3390/atmos15111321 - 2 Nov 2024
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Abstract
One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise [...] Read more.
One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise higher than expected and pose a flood risk to coastal low-lying areas. In Hong Kong, specifically when the northeast monsoon coincides with the higher spring tides in late autumn and winter, and sometimes even compounded by the storm surge brought by late-season tropical cyclones (TCs), the result may be coastal flooding or sea inundation. Aiming at forecasting such sea level anomalies on the scale of hours and days with local tide gauges using a flexible and computationally efficient method, this study adapts a data-driven method based on empirical orthogonal functions (EOF) regression of non-uniformly lagged regional wind field from ECMWF Reanalysis v5 (ERA5) to capture the effects from synoptic weather evolution patterns, excluding the effect of TCs. Local atmospheric pressure and winds are also included in the predictors of the regression model. Verification results show good performance in general. Hindcast using ECMWF forecasts as input reveals that the reduction of mean absolute error (MAE) by adding the anomaly forecast to the existing predicted astronomical tide was as high as 30% in February on average over the whole range of water levels, as well as that compared against the Delft3D forecast in a strong northeast monsoon case. The EOF method generally outperformed the persistence method in forecasting water level anomaly for a lead time of more than 6 h. The performance was even better particularly for high water levels, making it suitable to serve as a forecast reference tool for providing high water level alerts to relevant emergency response agencies to tackle the risk of coastal inundation in non-TC situations and an estimate of the anomaly contribution from the northeast monsoon under its combined effect with TC. The model is capable of improving water level forecasts up to a week ahead, despite the general decreasing model performance with increasing lead time due to less accurate input from model forecasts at a longer range. Some cases show that the model successfully predicted both positive and negative anomalies with a magnitude similar to observations up to 5 to 7 days in advance. Full article
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