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Journal articles on the topic 'Air sea interaction'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Seo, Hyodae, Larry W. O’Neill, Mark A. Bourassa, et al. "Ocean Mesoscale and Frontal-Scale Ocean–Atmosphere Interactions and Influence on Large-Scale Climate: A Review." Journal of Climate 36, no. 7 (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

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2

Long, David G., and David Arnold. "Observational research in air/sea interaction." Remote Sensing Reviews 8, no. 1-3 (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 (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 (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 (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 (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 forc

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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 (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, et al. "Interaction of Air and Sea above Seamount in the Halmahera Sea." IOP Conference Series: Earth and Environmental Science 1047, no. 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 o

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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 (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 (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 calcul

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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, et al. "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 (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 (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, et al. "Air–sea interaction over ocean fronts and eddies." Dynamics of Atmospheres and Oceans 45, no. 3-4 (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 (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, et al. "Tropical air-sea interaction in general circulation models." Climate Dynamics 7, no. 2 (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, et al. "Air–Sea/Land Interaction in the Coastal Zone." Boundary-Layer Meteorology 167, no. 2 (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 (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 uncouple

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25

Drennan, W. M., H. C. Graber, C. O. Collins, et al. "EASI: An Air–Sea Interaction Buoy for High Winds." Journal of Atmospheric and Oceanic Technology 31, no. 6 (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 (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

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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 (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 (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

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29

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 (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 Wate

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30

Rutgersson, Anna, Heidi Pettersson, Erik Nilsson, et al. "Using land-based stations for air–sea interaction studies." Tellus A: Dynamic Meteorology and Oceanography 72, no. 1 (2019): 1–23. http://dx.doi.org/10.1080/16000870.2019.1697601.

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31

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

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32

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 (2008): n/a. http://dx.doi.org/10.1029/2008gl033942.

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33

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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34

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 (1989): 354–65. http://dx.doi.org/10.1175/1520-0477(1989)070<0354:tnrlas>2.0.co;2.

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35

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 (1990): 514–19. http://dx.doi.org/10.1175/1520-0477(1990)071<0514:pfcasi>2.0.co;2.

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36

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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37

Gat, J. R., B. Klein, Y. Kushnir, et al. "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 (2011): 953–65. http://dx.doi.org/10.3402/tellusb.v55i5.16395.

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38

GAT, J. R., B. KLEIN, Y. KUSHNIR, et al. "Isotope composition of air moisture over the Mediterranean Sea: an index of the air-sea interaction pattern." Tellus B 55, no. 5 (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 (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 g

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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 (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 g

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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 (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 intera

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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 (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 (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 (2013): 3462–67. http://dx.doi.org/10.1002/grl.50641.

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45

Yang, Lei, Dongxiao Wang, Jian Huang, 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 (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

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46

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 (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

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47

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 (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 scale

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48

Marullo, Salvatore, Jaime Pitarch, Marco Bellacicco, et al. "Air–Sea Interaction in the Central Mediterranean Sea: Assessment of Reanalysis and Satellite Observations." Remote Sensing 13, no. 11 (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

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49

Zhang, Wei, Yulong Yao, Duo Chan, and Jie Feng. "Advances in Air–Sea Interactions, Climate Variability, and Predictability." Atmosphere 15, no. 12 (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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50

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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