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Journal articles on the topic 'Air sea interaction'

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Published: 4 June 2021

Last updated: 9 June 2025

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1

Seo, Hyodae, Larry W. O’Neill, Mark A. Bourassa, Arnaud Czaja, Kyla Drushka, James B. Edson, Baylor Fox-Kemper, et al. "Ocean Mesoscale and Frontal-Scale Ocean–Atmosphere Interactions and Influence on Large-Scale Climate: A Review." Journal of Climate 36, no. 7 (April 1, 2023): 1981–2013. http://dx.doi.org/10.1175/jcli-d-21-0982.1.

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Abstract Two decades of high-resolution satellite observations and climate modeling studies have indicated strong ocean–atmosphere coupled feedback mediated by ocean mesoscale processes, including semipermanent and meandrous SST fronts, mesoscale eddies, and filaments. The air–sea exchanges in latent heat, sensible heat, momentum, and carbon dioxide associated with this so-called mesoscale air–sea interaction are robust near the major western boundary currents, Southern Ocean fronts, and equatorial and coastal upwelling zones, but they are also ubiquitous over the global oceans wherever ocean mesoscale processes are active. Current theories, informed by rapidly advancing observational and modeling capabilities, have established the importance of mesoscale and frontal-scale air–sea interaction processes for understanding large-scale ocean circulation, biogeochemistry, and weather and climate variability. However, numerous challenges remain to accurately diagnose, observe, and simulate mesoscale air–sea interaction to quantify its impacts on large-scale processes. This article provides a comprehensive review of key aspects pertinent to mesoscale air–sea interaction, synthesizes current understanding with remaining gaps and uncertainties, and provides recommendations on theoretical, observational, and modeling strategies for future air–sea interaction research. Significance Statement Recent high-resolution satellite observations and climate models have shown a significant impact of coupled ocean–atmosphere interactions mediated by small-scale (mesoscale) ocean processes, including ocean eddies and fronts, on Earth’s climate. Ocean mesoscale-induced spatial temperature and current variability modulate the air–sea exchanges in heat, momentum, and mass (e.g., gases such as water vapor and carbon dioxide), altering coupled boundary layer processes. Studies suggest that skillful simulations and predictions of ocean circulation, biogeochemistry, and weather events and climate variability depend on accurate representation of the eddy-mediated air–sea interaction. However, numerous challenges remain in accurately diagnosing, observing, and simulating mesoscale air–sea interaction to quantify its large-scale impacts. This article synthesizes the latest understanding of mesoscale air–sea interaction, identifies remaining gaps and uncertainties, and provides recommendations on strategies for future ocean–weather–climate research.

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2

Long, David G., and David Arnold. "Observational research in air/sea interaction." Remote Sensing Reviews 8, no. 1-3 (January 1994): 189–94. http://dx.doi.org/10.1080/02757259309532194.

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3

Renfrew, I. "Air-sea interaction: Laws and mechanisms." Eos, Transactions American Geophysical Union 82, no. 50 (2001): 626. http://dx.doi.org/10.1029/01eo00364.

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4

Csanady,, GT, and JL Lumley,. "Air-Sea Interaction: Laws and Mechanisms." Applied Mechanics Reviews 55, no. 6 (October 16, 2002): B117. http://dx.doi.org/10.1115/1.1508156.

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5

Chao, Shenn-Yu. "An Air-Sea Interaction Model for Cold-Air Outbreaks." Journal of Physical Oceanography 22, no. 8 (August 1992): 821–42. http://dx.doi.org/10.1175/1520-0485(1992)022<0821:aasimf>2.0.co;2.

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6

Ji, Zhen-Gang, and Ji-Ping Chao. "An analytical coupled air-sea interaction model." Journal of Marine Systems 1, no. 3 (January 1991): 263–70. http://dx.doi.org/10.1016/0924-7963(91)90032-p.

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7

Bishop, Stuart P., R. Justin Small, Frank O. Bryan, and Robert A. Tomas. "Scale Dependence of Midlatitude Air–Sea Interaction." Journal of Climate 30, no. 20 (September 13, 2017): 8207–21. http://dx.doi.org/10.1175/jcli-d-17-0159.1.

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Abstract It has traditionally been thought that midlatitude sea surface temperature (SST) variability is predominantly driven by variations in air–sea surface heat fluxes (SHFs) associated with synoptic weather variability. Here it is shown that in regions marked by the highest climatological SST gradients and SHF loss to the atmosphere, the variability in SST and SHF at monthly and longer time scales is driven by internal ocean processes, termed here “oceanic weather.” This is shown within the context of an energy balance model of coupled air–sea interaction that includes both stochastic forcing for the atmosphere and ocean. The functional form of the lagged correlation between SST and SHF allows us to discriminate between variability that is driven by atmospheric versus oceanic weather. Observations show that the lagged functional relationship of SST–SHF and SST tendency–SHF correlation is indicative of ocean-driven SST variability in the western boundary currents (WBCs) and the Antarctic Circumpolar Current (ACC). By applying spatial and temporal smoothing, thereby dampening the signature SST anomalies generated by eddy stirring, it is shown that the oceanic influence on SST variability increases with time scale but decreases with increasing spatial scale. The scale at which SST variability in the WBCs and the ACC transitions from ocean to atmosphere driven occurs at scales less than 500 km. This transition scale highlights the need to resolve mesoscale eddies in coupled climate models to adequately simulate the variability of air–sea interaction. Away from strong SST fronts the lagged functional relationships are indicative of the traditional paradigm of atmospherically driven SST variability.

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8

Rodwell, M. J., and C. K. Folland. "Atlantic air–sea interaction and seasonal predictability." Quarterly Journal of the Royal Meteorological Society 128, no. 583 (July 2002): 1413–43. http://dx.doi.org/10.1002/qj.200212858302.

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9

Tozuka, Tomoki. "Seasonal Air-Sea Interaction in the Tropics." Oceanography in Japan 15, no. 6 (2006): 455–63. https://doi.org/10.5928/kaiyou.15.6_455.

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10

Sobaruddin, D. P., F. Marpaung, R. A. B. Putra, A. Fahim, C. S. Dharma, D. T. Pramono, and A. Kristiawan. "Interaction of Air and Sea above Seamount in the Halmahera Sea." IOP Conference Series: Earth and Environmental Science 1047, no. 1 (July 1, 2022): 012009. http://dx.doi.org/10.1088/1755-1315/1047/1/012009.

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Abstract The interaction of sea and air plays a very important role in the early stages of cloud formation. In certain cases, changes in temperature in the sea surface layer and the atmospheric layer closest to the sea will affect the initiation of the formation of water vapor which can become cloud. To monitor the sea-air temperature interaction above Seamount in Halmahera Sea, we took an expedition of Jala Citra-I 2021 Aurora from August 28 to September 9, 2021 using The Indonesian Navy Center for Hydrography and Oceanography research vessel, the Navy’s KRI Spica-934. Weather condition was observed using two installed Automatic Weather Stations (AWS) mounted on a vessel, radiosonde in Sorong, West Papua, and Outgoing Longwave Radiation (OLR) data from NOAA (National Oceanic and Atmospheric Administration), while the profile of sea surface temperature (SST) were observed using a 24-hour CTD measurement. Both AWS data were analyzed using two samples Kolmogorov-Smirnov test with h=1 and showed low correlations (r2 = 0.2-0.4, p-value <0.01) for the parameters of temperature, relative humidity, and wind speed. The hourly SST ranged 29°C – 30°C from 0-50 meter and the Lifting Condensation Level ranged about 939 to 985 mb in the morning on 1 - 2 September. The OLR was a neutral and positive values. These conditions indicated that a strong local effect dominantly created by a strong sea-air interaction in the study area. A warm SST with a strong divergence wind leads a warm air layer developed on the sea surface to rise. A low OLR with a moderate CAPE is enough to support the updraft of water vapor, rising from sea surface and then support convective activity formed in the region. In addition, it shows that the changes activity of convective clouds, developing over warm waters, are dominant mode of diurnal variability. However, investigation of intra-seasonal variability in Halmahera Sea was not clear. Further investigation on spatiotemporal of sea-air interaction on a local scale are needed to capture the phenomena on its season.

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11

Renfrew, Ian A., and G. W. K. Moore. "An Extreme Cold-Air Outbreak over the Labrador Sea: Roll Vortices and Air–Sea Interaction." Monthly Weather Review 127, no. 10 (October 1999): 2379–94. http://dx.doi.org/10.1175/1520-0493(1999)127<2379:aecaoo>2.0.co;2.

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12

Cerovečki, Ivana, and John Marshall. "Eddy Modulation of Air–Sea Interaction and Convection." Journal of Physical Oceanography 38, no. 1 (January 1, 2008): 65–83. http://dx.doi.org/10.1175/2007jpo3545.1.

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Abstract Eddy modulation of the air–sea interaction and convection that occurs in the process of mode water formation is analyzed in simulations of a baroclinically unstable wind- and buoyancy-driven jet. The watermass transformation analysis of Walin is used to estimate the formation rate of mode water and to characterize the role of eddies in that process. It is found that diabatic eddy heat flux divergences in the mixed layer are comparable in magnitude, but of opposite sign, to the surface air–sea heat flux and largely cancel the direct effect of buoyancy loss to the atmosphere. The calculations suggest that mode water formation estimates based on climatological air–sea heat flux data and outcrops, which do not fully resolve ocean eddies, may neglect a large opposing term in the heat budget and are thus likely to significantly overestimate true formation rates. In Walin’s watermass transformation framework, this manifests itself as a sensitivity of formation rate estimates to the averaging period over which the outcrops and air–sea fluxes are subjected. The key processes are described in terms of a transformed Eulerian-mean formalism in which eddy-induced mean flow tends to cancel the Eulerian-mean flow, resulting in weaker residual mean flow, subduction, and mode water formation rates.

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13

Bourassa, Mark. "BOOK REVIEW | Air-Sea Interaction: Laws and Mechanisms." Oceanography 16, no. 3 (2003): 139. http://dx.doi.org/10.5670/oceanog.2003.48.

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14

Weller, Robert, J. Thomas Farrar, Jared Buckley, Simi Matthew, R. Venkatesan, J. Sree Lekha, Dipanjan Chaudhuri, N. Suresh Kumar, and B. Praveen Kuman. "Air-Sea Interaction in the Bay of Bengal." Oceanography 29, no. 2 (2016): 28–37. http://dx.doi.org/10.5670/oceanog.2016.36.

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15

Zebiak, Stephen E. "Air–Sea Interaction in the Equatorial Atlantic Region." Journal of Climate 6, no. 8 (August 1993): 1567–86. http://dx.doi.org/10.1175/1520-0442(1993)006<1567:aiitea>2.0.co;2.

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16

Charnock, H., and J. A. Businger. "The Frontal Air-Sea Interaction Experiment in perspective." Journal of Geophysical Research 96, no. C5 (1991): 8639. http://dx.doi.org/10.1029/91jc00323.

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17

Rogers, David P. "Air-sea interaction: Connecting the ocean and atmosphere." Reviews of Geophysics 33, S2 (July 1995): 1377–83. http://dx.doi.org/10.1029/95rg00255.

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18

Brown, R. A. "On satellite scatterometer capabilities in air-sea interaction." Journal of Geophysical Research 91, no. C2 (1986): 2221. http://dx.doi.org/10.1029/jc091ic02p02221.

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19

Williams, Richard G. "Modification of ocean eddies by air-sea interaction." Journal of Geophysical Research 93, no. C12 (1988): 15523. http://dx.doi.org/10.1029/jc093ic12p15523.

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20

Small, R. J., S. P. deSzoeke, S. P. Xie, L. O’Neill, H. Seo, Q. Song, P. Cornillon, M. Spall, and S. Minobe. "Air–sea interaction over ocean fronts and eddies." Dynamics of Atmospheres and Oceans 45, no. 3-4 (August 2008): 274–319. http://dx.doi.org/10.1016/j.dynatmoce.2008.01.001.

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21

Kraus, Eric B. "Some problems in sub-mesoscale air-sea interaction." Journal of Marine Systems 5, no. 2 (July 1994): 101–10. http://dx.doi.org/10.1016/0924-7963(94)90025-6.

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22

Neelin, J. D., M. Latif, M. A. F. Allaart, M. A. Cane, U. Cubasch, W. L. Gates, P. R. Gent, et al. "Tropical air-sea interaction in general circulation models." Climate Dynamics 7, no. 2 (March 1992): 73–104. http://dx.doi.org/10.1007/bf00209610.

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23

Grachev, Andrey A., Laura S. Leo, Harindra J. S. Fernando, Christopher W. Fairall, Edward Creegan, Byron W. Blomquist, Adam J. Christman, and Christopher M. Hocut. "Air–Sea/Land Interaction in the Coastal Zone." Boundary-Layer Meteorology 167, no. 2 (December 5, 2017): 181–210. http://dx.doi.org/10.1007/s10546-017-0326-2.

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24

Qian, Huang, Yao Suxiang, and Zhang Yaocun. "Analysis of Local Air–Sea Interaction in East Asia Using a Regional Air–Sea Coupled Model." Journal of Climate 25, no. 2 (January 15, 2012): 767–76. http://dx.doi.org/10.1175/2011jcli3783.1.

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Abstract A regional air–sea coupled climate model based on the third regional climate model (RegCM3) and the regional oceanic model [the Princeton Ocean Model (POM)] is used to analyze the local air–sea interaction over East Asia in this study. The results indicate that the simulated sea surface temperature (SST) of the coupled model RegCM3–POM is reasonably accurate, and that the spatial pattern and temporal variation are consistent with that of the Global Sea Ice and Sea Surface Temperature dataset (GISST). The correlation between the SST and the atmospheric variables shows that the uncoupled model RegCM3 forced by the given SST cannot reproduce the real-time and SST lag correlation between SST and precipitation, and between SST and surface wind speed, whereas the relationship in the coupled model RegCM3–POM is reasonably accurate. RegCM3–POM reflects the air–sea interaction in the South China Sea and western Pacific Ocean, where the SST lead correlation is the inverse of the SST lag correlation between SST and precipitation, and strong winds bring warm water to the midlatitudes, so the correlation between wind speed and SST is negative in low latitudes and positive in the Kuroshio area. The uncoupled model fails to reproduce the effect of the atmosphere on the ocean. The further study on air–sea interaction in the South China Sea indicates that the earlier warm seawater corresponds to strong sensible heat flux, evaporation, precipitation, and weak net solar radiation, and the early strong sensible heat flux, evaporation, wind at the 10-m level, and weak net solar radiation cause the cold SST.

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25

Drennan, W. M., H. C. Graber, C. O. Collins, A. Herrera, H. Potter, R. J. Ramos, and N. J. Williams. "EASI: An Air–Sea Interaction Buoy for High Winds." Journal of Atmospheric and Oceanic Technology 31, no. 6 (June 1, 2014): 1397–409. http://dx.doi.org/10.1175/jtech-d-13-00201.1.

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Abstract This paper describes the new Extreme Air–Sea Interaction (EASI) buoy designed to measure direct air–sea fluxes, as well as mean properties of the lower atmosphere, upper ocean, and surface waves in high wind and wave conditions. The design of the buoy and its associated deep-water mooring are discussed. The performance of EASI during its 2010 deployment off Taiwan, where three typhoons were encountered, is summarized.

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26

Shuckburgh, Emily, Guillaume Maze, David Ferreira, John Marshall, Helen Jones, and Chris Hill. "Mixed Layer Lateral Eddy Fluxes Mediated by Air–Sea Interaction." Journal of Physical Oceanography 41, no. 1 (January 1, 2011): 130–44. http://dx.doi.org/10.1175/2010jpo4429.1.

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Abstract The modulation of air–sea heat fluxes by geostrophic eddies due to the stirring of temperature at the sea surface is discussed and quantified. It is argued that the damping of eddy temperature variance by such air–sea fluxes enhances the dissipation of surface temperature fields. Depending on the time scale of damping relative to that of the eddying motions, surface eddy diffusivities can be significantly enhanced over interior values. The issues are explored and quantified in a controlled setting by driving a tracer field, a proxy for sea surface temperature, with surface altimetric observations in the Antarctic Circumpolar Current (ACC) of the Southern Ocean. A new, tracer-based diagnostic of eddy diffusivity is introduced, which is related to the Nakamura effective diffusivity. Using this, the mixed layer lateral eddy diffusivities associated with (i) eddy stirring and small-scale mixing and (ii) surface damping by air–sea interaction is quantified. In the ACC, a diffusivity associated with surface damping of a comparable magnitude to that associated with eddy stirring (∼500 m2 s−1) is found. In frontal regions prevalent in the ACC, an augmentation of surface lateral eddy diffusivities of this magnitude is equivalent to an air–sea flux of 100 W m−2 acting over a mixed layer depth of 100 m, a very significant effect. Finally, the implications for other tracer fields such as salinity, dissolved gases, and chlorophyll are discussed. Different tracers are found to have surface eddy diffusivities that differ significantly in magnitude.

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27

Cotton, Jeremy H., and Kelvin J. Michael. "The monitoring of katabatic wind-coastal polynya interaction using AVHRR imagery." Antarctic Science 6, no. 4 (December 1994): 537–40. http://dx.doi.org/10.1017/s0954102094000799.

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Coastal polynyas, which form around the Antarctic coast due to persistent katabatic winds, play an important role in enhancing air-sea interaction. This paper discusses how thermal imagery from the Advanced Very High Resolution Radiometer (AVHRR) can be used to track the direction of katabatic winds, and hence facilitate research into air-sea interaction.

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28

Moulin, A., and A. Wirth. "A Drag-Induced Barotropic Instability in Air–Sea Interaction." Journal of Physical Oceanography 44, no. 2 (February 1, 2014): 733–41. http://dx.doi.org/10.1175/jpo-d-13-097.1.

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Abstract A new mechanism that induces barotropic instability in the ocean is discussed. It is due to the air–sea interaction with a quadratic drag law and horizontal viscous dissipation in the atmosphere. The authors show that the instability spreads to the atmosphere. The preferred spatial scale of the instability is that of the oceanic baroclinic Rossby radius of deformation. It can only be represented in numerical models, when the dynamics at this scale is resolved in the atmosphere and ocean. The dynamics are studied using two superposed shallow water layers: one for the ocean and one for the atmosphere. The interaction is due to the shear between the two layers. The shear applied to the ocean is calculated using the velocity difference between the ocean and the atmosphere and the quadratic drag law. In one-way interaction, the shear applied to the atmosphere neglects the ocean dynamics; it is calculated using the atmospheric wind only. In two-way interaction, it is opposite to the shear applied to the ocean. In one-way interaction, the atmospheric shear leads to a barotropic instability in the ocean. The instability in the ocean is amplified, in amplitude and scale, in two-way interaction and also triggers an instability in the atmosphere.

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29

Rutgersson, Anna, Heidi Pettersson, Erik Nilsson, Hans Bergström, Marcus B. Wallin, E. Douglas Nilsson, Erik Sahlée, Lichuan Wu, and E. Monica Mårtensson. "Using land-based stations for air–sea interaction studies." Tellus A: Dynamic Meteorology and Oceanography 72, no. 1 (December 9, 2019): 1–23. http://dx.doi.org/10.1080/16000870.2019.1697601.

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30

Panin, Gennady N., and Thomas Foken. "Air–sea interaction including a shallow and coastal zone." Journal of Atmospheric & Ocean Science 10, no. 3 (September 2005): 289–305. http://dx.doi.org/10.1080/17417530600787227.

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31

Wu, Chau-Ron, Yu-Lin Chang, Lie-Yauw Oey, C. W. June Chang, and Yi-Chia Hsin. "Air-sea interaction between tropical cyclone Nari and Kuroshio." Geophysical Research Letters 35, no. 12 (June 25, 2008): n/a. http://dx.doi.org/10.1029/2008gl033942.

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32

Bane, John M., and Kenric E. Osgood. "Wintertime air-sea interaction processes across the Gulf Stream." Journal of Geophysical Research 94, no. C8 (1989): 10755. http://dx.doi.org/10.1029/jc094ic08p10755.

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33

Blanc, Theodore V., William J. Plant, and William C. Keller. "The Naval Research Laboratory's Air-Sea Interaction Blimp Experiment." Bulletin of the American Meteorological Society 70, no. 4 (April 1989): 354–65. http://dx.doi.org/10.1175/1520-0477(1989)070<0354:tnrlas>2.0.co;2.

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34

Bane, John M., Clinton D. Winant, and James E. Overland. "Planning for Coastal Air-Sea Interaction Studies in CoPO." Bulletin of the American Meteorological Society 71, no. 4 (April 1990): 514–19. http://dx.doi.org/10.1175/1520-0477(1990)071<0514:pfcasi>2.0.co;2.

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35

Weller, Robert A. "Overview of the Frontal Air-Sea Interaction Experiment (FASINEX): A study of air-sea interaction in a region of strong oceanic gradients." Journal of Geophysical Research 96, no. C5 (1991): 8501. http://dx.doi.org/10.1029/90jc01868.

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36

Andreas, Edgar L., and Larry Mahrt. "On the Prospects for Observing Spray-Mediated Air–Sea Transfer in Wind–Water Tunnels." Journal of the Atmospheric Sciences 73, no. 1 (December 21, 2015): 185–98. http://dx.doi.org/10.1175/jas-d-15-0083.1.

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Abstract Nature is wild, unconstrained, and often dangerous. In particular, studying air–sea interaction in winds typical of tropical cyclones can place researchers, their instruments, and even their research platforms in jeopardy. As an alternative, laboratory wind–water tunnels can probe 10-m equivalent winds of hurricane strength under conditions that are well constrained and place no personnel or equipment at risk. Wind–water tunnels, however, cannot simulate all aspects of air–sea interaction in high winds. The authors use here the comprehensive data from the Air–Sea Interaction Salt Water Tank (ASIST) wind–water tunnel at the University of Miami that Jeong, Haus, and Donelan published in this journal to demonstrate how spray-mediated processes are different over the open ocean and in wind tunnels. A key result is that, at all high-wind speeds, the ASIST tunnel was able to quantify the so-called interfacial air–sea enthalpy flux—the flux controlled by molecular processes right at the air–water interface. This flux cannot be measured in high winds over the open ocean because the ubiquitous spray-mediated enthalpy transfer confounds the measurements. The resulting parameterization for this interfacial flux has implications for modeling air–sea heat fluxes from moderate winds to winds of hurricane strength.

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37

Gat, J. R., B. Klein, Y. Kushnir, W. Roether, H. Wernli, R. Yam, and A. Shemesh. "Isotope composition of air moisture over the Mediterranean Sea: an index of the air-sea interaction pattern." Tellus B: Chemical and Physical Meteorology 55, no. 5 (December 30, 2011): 953–65. http://dx.doi.org/10.3402/tellusb.v55i5.16395.

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38

GAT, J. R., B. KLEIN, Y. KUSHNIR, W. ROETHER, H. WERNLI, R. YAM, and A. SHEMESH. "Isotope composition of air moisture over the Mediterranean Sea: an index of the air-sea interaction pattern." Tellus B 55, no. 5 (November 2003): 953–65. http://dx.doi.org/10.1034/j.1600-0889.2003.00081.x.

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39

Ibrayev, R. A., E. Özsoy, C. Schrum, and H. İ. Sur. "Seasonal variability of the Caspian Sea three-dimensional circulation, sea level and air-sea interaction." Ocean Science 6, no. 1 (March 3, 2010): 311–29. http://dx.doi.org/10.5194/os-6-311-2010.

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Abstract. A three-dimensional primitive equation model including sea ice thermodynamics and air-sea interaction is used to study seasonal circulation and water mass variability in the Caspian Sea under the influence of realistic mass, momentum and heat fluxes. River discharges, precipitation, radiation and wind stress are seasonally specified in the model, based on available data sets. The evaporation rate, sensible and latent heat fluxes at the sea surface are computed interactively through an atmospheric boundary layer sub-model, using the ECMWF-ERA15 re-analysis atmospheric data and model generated sea surface temperature. The model successfully simulates sea-level changes and baroclinic circulation/mixing features with forcing specified for a selected year. The results suggest that the seasonal cycle of wind stress is crucial in producing basin circulation. Seasonal cycle of sea surface currents presents three types: cyclonic gyres in December–January; Eckman south-, south-westward drift in February–July embedded by western and eastern southward coastal currents and transition type in August–November. Western and eastern northward sub-surface coastal currents being a result of coastal local dynamics at the same time play an important role in meridional redistribution of water masses. An important part of the work is the simulation of sea surface topography, yielding verifiable results in terms of sea level. The model successfully reproduces sea level variability for four coastal points, where the observed data are available. Analyses of heat and water budgets confirm climatologic estimates of heat and moisture fluxes at the sea surface. Experiments performed with variations in external forcing suggest a sensitive response of the circulation and the water budget to atmospheric and river forcing.

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40

Ibrayev, R. A., E. Özsoy, C. Schrum, and H. İ. Sur. "Seasonal variability of the Caspian Sea three-dimensional circulation, sea level and air-sea interaction." Ocean Science Discussions 6, no. 3 (September 1, 2009): 1913–70. http://dx.doi.org/10.5194/osd-6-1913-2009.

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Abstract. A three-dimensional primitive equation model including sea ice thermodynamics and air-sea interaction is used to study seasonal circulation and water mass variability in the Caspian Sea under the influence of realistic mass, momentum and heat fluxes. River discharges, precipitation, radiation and wind stress are seasonally specified in the model, based on available data sets. The evaporation rate, sensible and latent heat fluxes at the sea surface are computed interactively through an atmospheric boundary layer sub-model, using the ECMWF-ERA15 re-analysis atmospheric data and model generated sea surface temperature. The model successfully simulates sea-level changes and baroclinic circulation/mixing features with forcing specified for a selected year. The results suggest that the seasonal cycle of wind stress is crucial in producing basin circulation. Seasonal cycle of sea surface currents presents three types: cyclonic gyres in December–January; Eckman south-, south-westward drift in February–July embedded by western and eastern southward coastal currents and transition type in August–November. Western and eastern northward sub-surface coastal currents being a result of coastal local dynamics at the same time play an important role in meridional redistribution of water masses. An important part of the work is the simulation of sea surface topography, yielding verifiable results in terms of sea level. Model successfully reproduces sea level variability for four coastal points, where the observed data are available. Analyses of heat and water budgets confirm climatologic estimates of heat and moisture fluxes at the sea surface. Experiments performed with variations in external forcing suggest a sensitive response of the circulation and the water budget to atmospheric and river forcing.

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41

Bala Subrahamanyam, D., and R. Ramachandran. "Wind Speed dependence of Air-Sea Exchange parameters over the Indian Ocean during INDOEX, IFP-99." Annales Geophysicae 21, no. 7 (July 31, 2003): 1667–79. http://dx.doi.org/10.5194/angeo-21-1667-2003.

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Abstract. Air-Sea exchange of momentum, heat and moisture over the oceanic surface plays an important role in understanding several processes spanning various scales of atmospheric and oceanic motions. The present study provides estimates of air-sea exchange parameters along the cruise track of the Intensive Field Phase of Indian Ocean Experiment (INDOEX, IFP-99) conducted on board Oceanic Research Vessel (ORV) Sagar Kanya during 20 January–12 March 1999 for a large region of the Indian Ocean. The study is aimed at acquiring a better understanding of the wind speed dependence of air-sea interaction parameters, such as roughness lengths for wind (z0), temperature (z0t) and hu-midity (z0q), which play a key role in the determination of the air-sea exchange coefficients and interface fluxes across the tropical oceans. The variation of drag coefficient (CD), sensible heat and water vapor exchange coefficients (CH and CE), are also discussed in relation to the wind speed. An empirical relation is derived between the estimated values of drag coefficients and the observed values of wind speeds for the hitherto data-sparse regions over the tropical Indian Ocean.Key words. Oceanography: physical (air-sea interaction) Meteorology and atmospheric dynamics (ocean-atmosphere interaction) – Oceanography: physical (marine meteorology)

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42

Graber, Hans C., Eugene A. Terray, Mark A. Donelan, William M. Drennan, John C. Van Leer, and Donald B. Peters. "ASIS—A New Air–Sea Interaction Spar Buoy: Design and Performance at Sea." Journal of Atmospheric and Oceanic Technology 17, no. 5 (May 2000): 708–20. http://dx.doi.org/10.1175/1520-0426(2000)017<0708:aanasi>2.0.co;2.

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43

Khelif, Djamal, Carl A. Friehe, Haflidi Jonsson, Qing Wang, and Konstantinos Rados. "Wintertime boundary-layer structure and air–sea interaction over the Japan/East Sea." Deep Sea Research Part II: Topical Studies in Oceanography 52, no. 11-13 (June 2005): 1525–46. http://dx.doi.org/10.1016/j.dsr2.2004.04.005.

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44

Moore, G. W. K. "The Novaya Zemlya Bora and its impact on Barents Sea air-sea interaction." Geophysical Research Letters 40, no. 13 (July 1, 2013): 3462–67. http://dx.doi.org/10.1002/grl.50641.

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45

Marullo, Salvatore, Jaime Pitarch, Marco Bellacicco, Alcide Giorgio di Sarra, Daniela Meloni, Francesco Monteleone, Damiano Sferlazzo, Vincenzo Artale, and Rosalia Santoleri. "Air–Sea Interaction in the Central Mediterranean Sea: Assessment of Reanalysis and Satellite Observations." Remote Sensing 13, no. 11 (June 3, 2021): 2188. http://dx.doi.org/10.3390/rs13112188.

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Air–sea heat fluxes are essential climate variables, required for understanding air–sea interactions, local, regional and global climate, the hydrological cycle and atmospheric and oceanic circulation. In situ measurements of fluxes over the ocean are sparse and model reanalysis and satellite data can provide estimates at different scales. The accuracy of such estimates is therefore essential to obtain a reliable description of the occurring phenomena and changes. In this work, air–sea radiative fluxes derived from the SEVIRI sensor onboard the MSG satellite and from ERA5 reanalysis have been compared to direct high quality measurements performed over a complete annual cycle at the ENEA oceanographic observatory, near the island of Lampedusa in the Central Mediterranean Sea. Our analysis reveals that satellite derived products overestimate in situ direct observations of the downwelling short-wave (bias of 6.1 W/m2) and longwave (bias of 6.6 W/m2) irradiances. ERA5 reanalysis data show a negligible positive bias (+1.0 W/m2) for the shortwave irradiance and a large negative bias (−17 W/m2) for the longwave irradiance with respect to in situ observations. ERA5 meteorological variables, which are needed to calculate the air–sea heat flux using bulk formulae, have been compared with in situ measurements made at the oceanographic observatory. The two meteorological datasets show a very good agreement, with some underestimate of the wind speed by ERA5 for high wind conditions. We investigated the impact of different determinations of heat fluxes on the near surface sea temperature (1 m depth), as determined by calculations with a one-dimensional numerical model, the General Ocean Turbulence Model (GOTM). The sensitivity of the model to the different forcing was measured in terms of differences with respect to in situ temperature measurements made during the period under investigation. All simulations reproduced the true seasonal cycle and all high frequency variabilities. The best results on the overall seasonal cycle were obtained when using meteorological variables in the bulk formulae formulations used by the model itself. The derived overall annual net heat flux values were between +1.6 and 40.4 W/m2, depending on the used dataset. The large variability obtained with different datasets suggests that current determinations of the heat flux components and, in particular, of the longwave irradiance, need to be improved. The ENEA oceanographic observatory provides a complete, long-term, high resolution time series of high quality in situ observations. In the future, more similar sites worldwide will be needed for model and satellite validations and to improve the determination of the air–sea exchange and the understanding of related processes.

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Yang, Lei, Dongxiao Wang, Jian Huang, Xin Wang, Lili Zeng, Rui Shi, Yunkai He, et al. "Toward a Mesoscale Hydrological and Marine Meteorological Observation Network in the South China Sea." Bulletin of the American Meteorological Society 96, no. 7 (July 1, 2015): 1117–35. http://dx.doi.org/10.1175/bams-d-14-00159.1.

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Abstract Air–sea interaction in the South China Sea (SCS) has direct impacts on the weather and climate of its surrounding areas at various spatiotemporal scales. In situ observation plays a vital role in exploring the dynamic characteristics of the regional circulation and air–sea interaction. Remote sensing and regional modeling are expected to provide high-resolution data for studies of air–sea coupling; however, careful validation and calibration using in situ observations is necessary to ensure the quality of these data. Through a decade of effort, a marine observation network in the SCS has begun to be established, yielding a regional observatory for the air–sea synoptic system. Earlier observations in the SCS were scarce and narrowly focused. Since 2004, an annual series of scientific open cruises during late summer in the SCS has been organized by the South China Sea Institute of Oceanology (SCSIO), carefully designed based on the dynamic characteristics of the oceanic circulation and air–sea interaction in the SCS region. Since 2006, the cruise carried a radiometer and radiosondes on board, marking a new era of marine meteorological observation in the SCS. Fixed stations have been established for long-term and sustained records. Observations obtained through the network have been used to study regional ocean circulation and processes in the marine atmospheric boundary layer. In the future, a great number of multi-institutional, collaborative scientific cruises and observations at fixed stations will be carried out to establish a mesoscale hydrological and marine meteorological observation network in the SCS.

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47

Isobe, Atsuhiko, and Robert C. Beardsley. "Atmosphere and Marginal-Sea Interaction Leading to an Interannual Variation in Cold-Air Outbreak Activity over the Japan Sea." Journal of Climate 20, no. 23 (December 1, 2007): 5707–14. http://dx.doi.org/10.1175/2007jcli1779.1.

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Abstract The interannual variation in cold-air outbreak activity over the Japan Sea is investigated using Japan Meteorological Agency buoy 21002 and Quick Scatterometer (QuikSCAT) wind data, Japan Oceanographic Data Center sea surface temperature (SST) data, NCEP–NCAR reanalysis surface wind and sea level pressure (SLP) data, and the winter Arctic Oscillation (AO) index of Thompson and Wallace. Cold-air outbreaks occur during the “winter” November–March period, and wind data for this season for the 19-winter period 1981–2000 were analyzed. Wavelet spectra averaged between 5- and 15-day periods were used to evaluate the intensity of cold-air outbreaks quantitatively. The winter mean wavelet spectra exhibited a clear interannual variation and a significant positive correlation with the AO index, indicating that intensive cold-air outbreaks frequently occur during relatively warm winters caused by a quasi-decadal AO. Based on the SST and SLP data, the low atmospheric surface pressure disturbances tend to develop over the warm East China Sea in warm winters in the positive AO phase. As these low SLP disturbances advance toward the northern Japan islands during the positive AO phase, they intensify more, leading to stronger cold-air outbreaks over the Japan Sea and increased sea surface cooling over the northern Japan Sea.

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48

Hausmann, Ute, Arnaud Czaja, and John Marshall. "Estimates of Air–Sea Feedbacks on Sea Surface Temperature Anomalies in the Southern Ocean." Journal of Climate 29, no. 2 (January 7, 2016): 439–54. http://dx.doi.org/10.1175/jcli-d-15-0015.1.

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Abstract Sea surface temperature (SST) air–sea feedback strengths and associated decay time scales in the Southern Ocean (SO) are estimated from observations and reanalysis datasets of SST, air–sea heat fluxes, and ocean mixed layer depths. The spatial, seasonal, and scale dependence of the air–sea heat flux feedbacks is mapped in circumpolar bands and implications for SST persistence times are explored. It is found that the damping effect of turbulent heat fluxes dominates over that due to radiative heat fluxes. The turbulent heat flux feedback acts to damp SSTs in all bands and spatial scales and in all seasons, at rates varying between 5 and 25 W m−2 K−1, while the radiative heat flux feedback has a more uniform spatial distribution with a magnitude rarely exceeding 5 W m−2 K−1. In particular, the implied net air–sea feedback (turbulent + radiative) on SST south of the polar front, and in the region of seasonal sea ice, is as weak as 5–10 W m−2 K−1 in the summertime on large spatial scales. Air–sea interaction alone thus allows SST signals induced around Antarctica in the summertime to persist for several seasons. The damping effect of mixed layer entrainment on SST anomalies averages to approximately 20 W m−2 K−1 across the ACC bands in the summer-to-winter entraining season and thereby reduces summertime SST persistence to less than half of that predicted by air–sea interaction alone (i.e., 3–6 months).

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Zhang, Wei, Yulong Yao, Duo Chan, and Jie Feng. "Advances in Air–Sea Interactions, Climate Variability, and Predictability." Atmosphere 15, no. 12 (November 26, 2024): 1422. http://dx.doi.org/10.3390/atmos15121422.

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Air–sea interaction remains one of the most dynamic and influential components of the Earth’s climate system, significantly shaping the variability and predictability of both weather and climate [...]

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KAWAMURA, Ryuichi. "Climatic Variations in Relation to Large-scale Air-sea Interaction." Chigaku Zasshi (Jounal of Geography) 117, no. 6 (2008): 1063–76. http://dx.doi.org/10.5026/jgeography.117.1063.

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