Recent Advances in Air-Sea Interactions, Climate Variability, and Predictability

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

Deadline for manuscript submissions: closed (28 June 2024) | Viewed by 9324

Special Issue Editors

Princeton University and NOAA Global Systems Laboratory, Princeton, NJ 08540, USA
Interests: climate prediction; climate dynamics and modeling; air–sea interaction; extreme weather/climate; machine learning
Special Issues, Collections and Topics in MDPI journals
Woods Hole Oceanographic Institution, Falmouth, MA 02543, USA
Interests: climate data and reconstruction; climate dynamics; air–sea coupling; land–air coupling; machine learning
Special Issues, Collections and Topics in MDPI journals
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanography, Chinese Academy of Sciences, Guangzhou 510301, China
Interests: ocean’s role in climate change; marine heatwaves; coral bleaching
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Air–sea interaction is an active area of research that is crucial for reducing uncertainties in weather and climate predictions.  Exchanges of momentum, heat, and mass across the marine boundary layer involve a variety of dynamic, thermodynamic, and biogeochemical processes, and hence play an important role in the variability and predictability of weather and climate. Recent studies have shown advances in many respects, including, but not limited to:

(1) Improving air–sea coupling and exchange observations;
(2) Refining the representation of relevant processes in coupled climate models;
(3) Developing statistical representations using data-driven/ machine learning techniques;
(4) Understanding relevant physical processes from the submesoscale to mesoscale to synoptic scales and, further, to large-scale modes of climate variability;
(5) Addressing air–sea interaction in the context of climate change predictions at global and regional scales.

We hope to follow along these lines in this Special Issue. Therefore, we are inviting contributions covering the following topics: 

  • Air–sea interaction at the submeso, meso, and synoptic scales from the tropics to high latitudes;
  • Recent advances in the observation and modeling of air–sea coupling and exchange;
  • Large-scale modes of climate variability, such as ENSO, IOD, PDO, NAO, and AMO, and teleconnections;
  • High-resolution modeling of marine boundary layer processes;
  • Global and regional estimates of air–sea fluxes, including, but not limited to: heat, moisture, and momentum;
  • The influence of air–sea coupling on climate variability and predictability, including extreme weather and climate events;
  • Noval techniques involving air–sea interaction and coupling, including data-driven and machine learning approaches;
  • Other topics on air–sea interaction, climate dynamics, and predictability.

Dr. Wei Zhang
Dr. Duo Chan
Dr. Jie Feng
Dr. Yulong Yao
Guest Editors

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Keywords

  • air–sea interactions
  • submesoscale and mesoscale processes
  • climate dynamics and modeling
  • climate variability and predictability
  • extreme weather and climate
  • large-scale climate and teleconnections
  • observations and coupled modeling
  • high-resolution modeling
  • machine learning methods

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Published Papers (7 papers)

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Research

15 pages, 13755 KiB  
Article
Impact of El Niño-Southern Oscillation on Dust Variability during the Spring Season over the Arabian Peninsula
by Yazeed Alsubhi and Gohar Ali
Atmosphere 2024, 15(9), 1060; https://doi.org/10.3390/atmos15091060 - 2 Sep 2024
Viewed by 816
Abstract
This study investigates the dust aerosol optical depth (DAOD) variability over the Arabian Peninsula (AP) in the spring season, a region profoundly affected by dust activity due to its desert terrain. Employing the MERRA-2 DAOD reanalysis dataset for the period 1981–2022, a significant [...] Read more.
This study investigates the dust aerosol optical depth (DAOD) variability over the Arabian Peninsula (AP) in the spring season, a region profoundly affected by dust activity due to its desert terrain. Employing the MERRA-2 DAOD reanalysis dataset for the period 1981–2022, a significant trend in DAOD is noted in the spring season compared to the other seasons. The leading Empirical Orthogonal Function (EOF) explains 67% of the total DAOD variance during the spring season, particularly over the central and northeastern parts of AP. The analysis reveals the strengthening of upper-level divergence over the western Pacific, favoring mid-tropospheric positive geopotential height anomalies over the AP, leading to warm and drier surface conditions and increased DAOD. A statistically significant negative relationship (correlation = −0.32, at 95% confidence level) is noted between DAOD over AP and the El Niño-Southern Oscillation (ENSO), suggesting that La Niña conditions may favor higher dust concentrations over the AP region and vice versa during El Niño phase. The high (low) DAOD over the region corresponds to mid-tropospheric positive (negative) geopotential height anomalies through strengthening (weakening) of the upper-level divergence (convergence) over the western Pacific during the La Niña (El Niño) phase. This study shows that ENSO could be a possible precursor to predicting dust variability on a seasonal time scale. Full article
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15 pages, 7254 KiB  
Article
Northeast China Cold Vortex Amplifies Extreme Precipitation Events in the Middle and Lower Reaches Yangtze River Basin
by Hao Chen, Zuowei Xie, Xiaofeng He, Xiaodong Zhao, Zongting Gao, Biqiong Wu, Jun Zhang and Xiangxi Zou
Atmosphere 2024, 15(7), 819; https://doi.org/10.3390/atmos15070819 - 8 Jul 2024
Viewed by 765
Abstract
The middle and lower reaches of the Yangtze River (MLYR) frequently experience extreme precipitation events (EPEs) during June and July, the so-called Meiyu season. This study investigated EPEs in the MLYR during Meiyu seasons over 1961–2022, using rain gauge observations and ERA5 reanalysis [...] Read more.
The middle and lower reaches of the Yangtze River (MLYR) frequently experience extreme precipitation events (EPEs) during June and July, the so-called Meiyu season. This study investigated EPEs in the MLYR during Meiyu seasons over 1961–2022, using rain gauge observations and ERA5 reanalysis data. EPEs associated with the Northeast China cold vortex featured more undulating westerlies with a distinct wave train pattern from Europe to Northeast Asia. Due to robust Rossby wave energy, the trough deepened from Northeast China towards the MLYR and was confronted with a westward extension of the western Pacific subtropical high. Such a configuration enhanced the warm and moist monsoon conveyor belt and convergence of water vapor flux from southwestern China to the MLYR. The warm and moist air favored upward motion. The increased rainfall prevailed from southwestern China to the MLYR. In contrast, ordinary EPEs were characterized by zonal westerlies and weaker Rossby wave propagation. The Meiyu trough was comparatively shallow and confined to the MLYR with less westward expansion of the subtropical high. In response, the warm and moist monsoon conveyor belt was more localized, resulting in weaker EPEs in the MLYR. Full article
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17 pages, 10295 KiB  
Article
Interannual Fluctuations and Their Low-Frequency Modulation of Summertime Heavy Daily Rainfall Potential in Western Japan
by Takashi Mochizuki
Atmosphere 2024, 15(7), 814; https://doi.org/10.3390/atmos15070814 - 7 Jul 2024
Viewed by 925
Abstract
Heavy rainfall under the conditions of the changing climate has recently garnered considerable attention. The statistics on heavy daily rainfall offer vital information for assessing present and future extreme events and for clarifying the impacts of global climate variability and change, working to [...] Read more.
Heavy rainfall under the conditions of the changing climate has recently garnered considerable attention. The statistics on heavy daily rainfall offer vital information for assessing present and future extreme events and for clarifying the impacts of global climate variability and change, working to form a favorable background. By analyzing a set of large-ensemble simulations using a global atmospheric model, this study demonstrated that two different physical processes in global climate variability control the interannual fluctuations in the 99th- and 90th-percentile values of summertime daily rainfall (i.e., the potential amounts) on Kyushu Island in western Japan. The 90th-percentile values were closely related to large-scale horizontal moisture transport anomalies due to changes in the subtropical high in the northwestern Pacific, which was usually accompanied by basin-scale warming in the Indian Ocean subsequent to the wintertime El Niño events. The contributions of the sea surface temperatures over the northern Indian Ocean and the eastern tropical Pacific Ocean showed low-frequency modulations, mainly due to the influences of the global warming tendency and the interdecadal variability in the climate system, respectively. In contrast, tropical cyclone activity played a major role in changing the 99th-percentile value. The potentials of both the tropical cyclone intensity and the existence density fluctuated, largely owing to the summertime sea surface temperature over the tropical Pacific, which can be modulated by the El Niño diversity on interdecadal timescales. Full article
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24 pages, 4579 KiB  
Article
Investigating the Role of Wave Process in the Evaporation Duct Simulation by Using an Ocean–Atmosphere–Wave Coupled Model
by Zhigang Shan, Miaojun Sun, Wei Wang, Jing Zou, Xiaolei Liu, Hong Zhang, Zhijin Qiu, Bo Wang, Jinyue Wang and Shuai Yang
Atmosphere 2024, 15(6), 707; https://doi.org/10.3390/atmos15060707 - 13 Jun 2024
Viewed by 700
Abstract
In this study, a diagnostic model for evaporation ducts was established based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) and the Naval Postgraduate School (NPS) models. Utilizing this model, four sensitivity tests were conducted over the South China Sea from 21 September to 5 [...] Read more.
In this study, a diagnostic model for evaporation ducts was established based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) and the Naval Postgraduate School (NPS) models. Utilizing this model, four sensitivity tests were conducted over the South China Sea from 21 September to 5 October 2008, when four tropical cyclones affected the study domain. These tests were designed with different roughness schemes to investigate the impact mechanisms of wave processes on evaporation duct simulation under extreme weather conditions. The results indicated that wave processes primarily influenced the evaporation duct heights by altering sea surface roughness and dynamical factors. The indirect impacts of waves without dynamical factors were rather weak. Generally, a decrease in local roughness led to increased wind speed, decreased humidity, and a reduced air–sea temperature difference, resulting in the formation of evaporation ducts at higher altitudes. However, this affecting mechanism between roughness and evaporation ducts was also greatly influenced by changes in regional circulation. In the eastern open sea areas of the South China Sea, changes in evaporative ducts were more closely aligned with local impact mechanisms, whereas the changes in the central and western areas demonstrated greater complexity and fewer local impacts due to variations in regional circulation. Full article
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15 pages, 5518 KiB  
Article
Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR
by Davide Zanchettin, Kameswarrao Modali, Wolfgang A. Müller and Angelo Rubino
Atmosphere 2024, 15(3), 295; https://doi.org/10.3390/atmos15030295 - 28 Feb 2024
Viewed by 1143
Abstract
We use hindcasts from a state-of-the-art decadal climate prediction system initialized between 1979 and 2017 to explore the predictability of the Antarctic dipole—that is, the seesaw between sea ice cover in the Weddell and Ross Seas, and discuss its implications for Antarctic sea [...] Read more.
We use hindcasts from a state-of-the-art decadal climate prediction system initialized between 1979 and 2017 to explore the predictability of the Antarctic dipole—that is, the seesaw between sea ice cover in the Weddell and Ross Seas, and discuss its implications for Antarctic sea ice predictability. Our results indicate low forecast skills for the Antarctic dipole in the first hindcast year, with a strong relaxation of March values toward the climatology contrasting with an overestimation of anomalies in September, which we interpret as being linked to a predominance of local drift processes over initialized large-scale dynamics. Forecast skills for the Antarctic dipole and total Antarctic sea ice extent are uncorrelated. Limited predictability of the Antarctic dipole is also found under preconditioning around strong warm and strong cold events of the El Niño-Southern Oscillation. Initialization timing and model drift are reported as potential explanations for the poor predictive skills identified. Full article
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20 pages, 17629 KiB  
Article
Mesoscale Convective Systems and Extreme Precipitation on the West African Coast Linked to Ocean–Atmosphere Conditions during the Monsoon Period in the Gulf of Guinea
by Sandrine Djakouré, Joël Amouin, Kouassi Yves Kouadio and Modeste Kacou
Atmosphere 2024, 15(2), 194; https://doi.org/10.3390/atmos15020194 - 2 Feb 2024
Cited by 1 | Viewed by 1070
Abstract
This study investigates the importance of convective systems for extreme rainfall along the northern coast of the Gulf of Guinea (GG) and their relationship with atmospheric and oceanic conditions. Convective system data (MCSs), daily precipitation, sea surface temperature (SST) and moisture flux anomalies [...] Read more.
This study investigates the importance of convective systems for extreme rainfall along the northern coast of the Gulf of Guinea (GG) and their relationship with atmospheric and oceanic conditions. Convective system data (MCSs), daily precipitation, sea surface temperature (SST) and moisture flux anomalies from June to September 2007–2016 are used. The results show that 2/3 of MCSs crossing Abidjan are produced in June, which is the core of the major rainy season. Likewise, 2/3 of MCSs originate from continental areas, while 1/3 come from the ocean. Oceanic MCSs are mostly initiated close to the coast, which also corresponds to the Marine Heat Waves region. Continental MCSs are mostly initiated inland. The results also highlight the moisture flux contribution of three zones which have an impact on the onset and the sustaining of MCSs: (i) the seasonal migration of the intertropical convergence zone (ITCZ), (ii) the GG across the northern coastline, and finally (iii) the continent. These contributions of moisture fluxes coincide with oceanic warming off Northeast Brazil and the northern coast of the GG both two days before and the day of extreme rainfall events. The ocean contributes to moisten the atmosphere, and therefore to supply and sustain the MCSs during their lifecycle. Full article
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26 pages, 10597 KiB  
Article
NAO Seasonal Forecast Using a Multivariate Air–Sea Coupled Deep Learning Model Combined with Causal Discovery
by Bin Mu, Xin Jiang, Shijin Yuan, Yuehan Cui and Bo Qin
Atmosphere 2023, 14(5), 792; https://doi.org/10.3390/atmos14050792 - 26 Apr 2023
Cited by 4 | Viewed by 2417
Abstract
The North Atlantic Oscillation (NAO) is a major climatic phenomenon in the Northern Hemisphere, but the underlying air–sea interaction and physical mechanisms remain elusive. Despite successful short-term forecasts using physics-based numerical models, longer-term forecasts of NAO continue to pose a challenge. In this [...] Read more.
The North Atlantic Oscillation (NAO) is a major climatic phenomenon in the Northern Hemisphere, but the underlying air–sea interaction and physical mechanisms remain elusive. Despite successful short-term forecasts using physics-based numerical models, longer-term forecasts of NAO continue to pose a challenge. In this study, we employ advanced data-driven causal discovery techniques to explore the causality between multiple ocean–atmosphere processes and NAO. We identify the best NAO predictors based on this causality analysis and develop NAO-MCD, a multivariate air–sea coupled model that incorporates causal discovery to provide 1–6 month lead seasonal forecasts of NAO. Our results demonstrate that the selected predictors are strongly associated with NAO development, enabling accurate forecasts of NAO. NAO-MCD significantly outperforms conventional numerical models and provides reliable seasonal forecasts of NAO, particularly for winter events. Moreover, our model extends the range of accurate forecasts, surpassing state-of-the-art performance at 2- to 6-month lead-time NAO forecasts, substantially outperforming conventional numerical models. Full article
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