Skip to main content
Log in

Indirect air–sea interactions simulated with a coupled turbulence-resolving model

  • Published:
Ocean Dynamics Aims and scope Submit manuscript

Abstract

A turbulence-resolving parallelized atmospheric large-eddy simulation model (PALM) has been applied to study turbulent interactions between the humid atmospheric boundary layer (ABL) and the salt water oceanic mixed layer (OML). The most energetic three-dimensional turbulent eddies in the ABL–OML system (convective cells) were explicitly resolved in these simulations. This study considers a case of shear-free convection in the coupled ABL–OML system. The ABL–OML coupling scheme used the turbulent fluxes at the bottom of the ABL as upper boundary conditions for the OML and the sea surface temperature at the top of the OML as lower boundary conditions for the ABL. The analysis of the numerical experiment confirms that the ABL–OML interactions involve both the traditional direct coupling mechanism and much less studied indirect coupling mechanism (Garrett Dyn Atmos Ocean 23:19–34, 1996). The direct coupling refers to a common flux-gradient representation of the air–sea exchange, which is controlled by the temperature difference across the air–water interface. The indirect coupling refers to thermal instability of the Rayleigh–Benard convection, which is controlled by the temperature difference across the entire mixed layer through formation of the large convective eddies or cells. The indirect coupling mechanism in these simulations explained up to 45 % of the ABL–OML co-variability on the turbulent scales. Despite relatively small amplitude of the sea surface temperature fluctuations, persistence of the OML cells organizes the ABL convective cells. Water downdrafts in the OML cells tend to be collocated with air updrafts in the ABL cells. The study concludes that the convective structures in the ABL and the OML are co-organized. The OML convection controls the air–sea turbulent exchange in the quasi-equilibrium convective ABL–OML system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Abbreviations

c pa  = 1, 005 [J kg−1 K−1]:

specific heat capacity of air

c pw  = 4, 218 [J kg−1 K−1]:

specific heat capacity of water

L e  = 2,262.6108 103 [J kg−1]:

latent heat of evaporation

g = 9.81 [m s−2]:

gravity acceleration

ρ a  = 1.0 [kg m−3]:

density of air (stipulated)

ρ w   [kg m−3]:

potential density of sea water (calculated after Jackett et al. 2006)

θ va [K]:

virtual potential temperature of air

q [kg kg−1]:

absolute humidity of air

θ w [K]:

temperature of water

s [psu]:

water salinity

\( {\overrightarrow{u}}_a={u}_{ia}=\left({u}_a,{v}_a,{w}_a\right) \) [m s−1]:

velocity of air (zonal, meridional, and vertical components)

\( {\overrightarrow{u}}_w \) [m s−1]:

velocity of water

\( {u}_{*}={\left(\frac{\left|{\tau}_{ia}\right|}{\rho_a}\right)}^{1/2}={\left(\frac{\left|{\tau}_{iw}\right|}{\rho_w}\right)}^{1/2} \) [m s−1]:

surface friction velocity

\( {\tau}_{ia}={\rho}_a{\left({\left(\overline{u{\prime}_aw{\prime}_a},\kern0.5em \right)}^2+{\left(\overline{v{\prime}_aw{\prime}_a},\kern0.5em \right)}^2\right)}^{1/2} \) [kg s−2 m−1]:

vertical turbulent momentum flux in air; it is calculated at the ABL bottom boundary using the Monin–Obukhov relationships

\( {\tau}_{iw}={\rho}_w{\left({\left(\overline{u{\prime}_ww{\prime}_w}\right)}^2+{\left(\overline{v{\prime}_ww{\prime}_w}\right)}^2\right)}^{1/2} \) [kg s−2 m−1]:

vertical turbulent momentum flux in water; it is passed to the OML from the ABL as the boundary condition

F a  = F Sa  + F La [W m−2]:

total turbulent heat flux in air it is calculated at the ABL bottom boundary using the Monin–Obukhov relationships

\( {F}_{Sa}={\rho}_a{c}_{pa}\overline{w{\prime}_a\theta {\prime}_a} \) [W m−2]:

sensible heat flux in air

\( {F}_{La}={\rho}_a{L}_e\overline{w{\prime}_aq{\prime}_a} \) [W m−2]:

latent heat flux (ABL)

\( {F}_w={\rho}_w{c}_{pw}\overline{w{\prime}_w\theta {\prime}_w}\kern0.5em ={F}_a \) [W m−2]:

total turbulent heat flux in water; it is passed to the OML from the ABL as the boundary condition

\( B=-\frac{ g\alpha}{c_{pw}{\rho}_w}{F}_a+ g\beta s{\rho}_w\overline{w{\prime}_aq{\prime}_a} \) [W kg−1]:

buoyancy flux at the ABL–OML interface

\( \alpha =-\frac{1}{\rho}\frac{\partial \rho }{\partial \theta } \) [K−1]:

thermal expansion coefficient (α = 0.03 in air)

\( \beta =\frac{1}{\rho}\frac{\partial \rho }{\partial S} \) [psu−1]:

haline contraction coefficient

L = − u 3* /kF Sa ρ a c pa L = − u 3* /kF Sa ρ a c pa :

the Monin–Obukhov length scale in the ABL

k = 0.4:

Von Karman constant

References

  • Belmonte A, Libchaber A (1996) Thermal signature of plumes in turbulent convection: the skewness of the derivative. Phys Rev E 53(5):4893–4898

    Article  Google Scholar 

  • Brunke MA, Fairall CW, Zeng X, Eymard L, Curry JA (2003) Which bulk aerodynamic algorithms are least problematic in computing ocean surface turbulent fluxes? J Climate 16:619–635

    Article  Google Scholar 

  • Clayson CA, Bogdanoff AS (2013) The effect of diurnal sea surface temperature warming on climatological air–sea fluxes. J Climate 26:2546–2556

    Article  Google Scholar 

  • Clayson CA, Chen A (2002) Sensitivity of a coupled single-column model in the tropics to treatment of the interfacial parameterizations. J Climate 15(14):1805–1831

    Article  Google Scholar 

  • Clayson CA, Fairall CW, Curry JA (1996) Evaluation of turbulent fluxes at the ocean surface using surface renewal theory. J Geophys Res 101(C12):28503–28513

    Article  Google Scholar 

  • Deardorff JW (1980) Cloud top entrainment instability. J Atmos Sci 37:131–147

    Article  Google Scholar 

  • Deardorff JW, Willis GE (1985) Further results from a laboratory model of the convective planetary boundary layer. Boundary-Layer Meteorol 32:205–236

    Article  Google Scholar 

  • Edson J, Crawford T, Crescenti J, Farrar T, Frew N, Gerbi G, Helmis C, Hristov T, Khelif D, Jessup A, Jonsson H, Li M, Mahrt L, McGillis W, Plueddemann A, Shen L, Skyllingstad E, Stanton T, Sullivan P, Sun J, Trowbridge J, Vickers D, Wang S, Wang Q, Weller R, Wilkin J, Williams AJ, Yue DKP, Zappa C (2007) The coupled boundary layers and air–sea transfer experiment in low winds. Bull Am Meteorol Soc 88(3):341–356

    Article  Google Scholar 

  • Esau I (2003) Coriolis effect on coherent structures in planetary boundary layers. J Turbul 017

  • Esau I (2004) Simulation of Ekman boundary layers by large eddy model with dynamic mixed subfilter closure. Env Fluid Mech 4:273–303

    Article  Google Scholar 

  • Esau I (2007) Amplification of turbulent exchange over wide Arctic leads: large-eddy simulation study, J Geophys Res 112(D): D08109, doi:10.1029/2006JD007225

  • Esau I, Zilitinkevich SS (2006) Universal dependences between turbulent and mean flow parameters in stably and neutrally stratified planetary boundary layers. Nonlinear Processes Geophys 13:122–144

    Article  Google Scholar 

  • Esau I, Luhunga P, Djolov G, deW Rautenbach CJ, Zilitinkevich S (2012) Links between observed micrometeorological variability and land-use patterns in the highveld priority area of South Africa. Meteorol Atmos Phys 118(3):129–142. doi:10.1007/s00703-012-0218-4

    Article  Google Scholar 

  • Fairall CW, Bradley EF, Hare JE, Grachev AA (2003) Bulk parameterization of air–sea fluxes: updates and verification for COARE algorithm. J Climate 16:571–591

    Article  Google Scholar 

  • Fedorov KN, Ginzburg AI (1988) The subsurface layer of the ocean, Leningrad, Gidrometizdat, UdSSR, 303 p

  • Frankignoul C (1985) Sea surface temperature anomalies, planetary waves, and air–sea feedback in the middle latitudes. Rev Geophys 23(4):357–390

    Article  Google Scholar 

  • Garrett C (1996) Processes in the surface mixed layer of the ocean. Dyn Atmos Ocean 23:19–34

    Article  Google Scholar 

  • Glazunov AV, Lykossov VN (2003) Large-eddy simulation of interaction of ocean and atmospheric boundary layers. Russ J Numer Anal Math Model 18(4):279–295

    Article  Google Scholar 

  • Godfrey JS, Beljaars A (1991) On the turbulent fluxes of buoyancy, heat and moisture at the air–sea interface at low wind speed. J Geophys Res 96:22043–22048

    Article  Google Scholar 

  • Goh G, Noh Y (2013) Influence of the Coriolis force on the formation of a seasonal thermocline. Ocean Dyn 63:1083–1092

    Article  Google Scholar 

  • Gulev SK, Latif M, Keenlyside N, Park W, Koltermann KP (2013) North Atlantic Ocean control on surface heat flux on multidecadal timescales. Nature 499:464–467

    Article  Google Scholar 

  • Halkides D, Lee T, Kida S (2011) Mechanisms controlling the seasonal mixed layer temperature and salinity of the Indonesian seas. Ocean Dyn 61:481–495

    Article  Google Scholar 

  • Handler RA, Smith GB, Leighton RI (2001) The thermal structure of an air–water interface at low wind speeds. Tellus 53A:233–244

    Article  Google Scholar 

  • Hartmann J, Kottmeier C, Raasch S (1997) Roll vortices and boundary-layer development during a cold air outbreak. Boundary-Layer Meteorol 84:45–65

    Article  Google Scholar 

  • Hasson AEA, Deleroix T, Dussin R (2013) An assessment of the mixed layer salinity budget in the tropical Pacific Ocean. Observations and modeling (1990–2009). Ocean Dyn. doi:10.1007/s10236-013-0596-2

    Google Scholar 

  • Hellsten A, Zilitinkevich S (2013) Role of convective structures and background turbulence in the dry convective boundary layer. Boundary-Layer Meteorol 149:323–353. doi:10.1007/s10546-013-9854-6

    Article  Google Scholar 

  • Hogan RJ, Grant ALM, Illingworth AJ, Pearson GN, O’Connor EJ (2009) Vertical velocity variance and skewness in clear and cloud-topped boundary layers as revealed by Doppler lidar. Q J R Meteorol Soc 135:635–643

    Article  Google Scholar 

  • Jackett DR, McDougall TJ, Feistel R, Wright DG, Griffies SM (2006) Algorithms for density, potential temperature, conservative temperature, and freezing temperature of seawater. J Atmos Oceanic Tech 23:1709–1728

    Article  Google Scholar 

  • Kawai Y, Wada A (2007) Diurnal sea surface temperature variation and its impact on the atmosphere and ocean: a review. J Oceanogr 63:721–744

    Article  Google Scholar 

  • Kelly M, Wyngaard JC, Sullivan PP (2009) Application of a subfilter-scale flux model over the ocean using OHATS field data. J Atmos Sci 66:3217–3225

    Article  Google Scholar 

  • Lakehal D, Fulgosi M, Banerjee S, Yadigaroglu G (2008) Turbulence and heat exchange in considering vapor–liquid flow. Phys Fluids 20:065101

    Article  Google Scholar 

  • Lebedev I, Redelsperger J-L, Tomczak M (2001) Tropical ocean response to atmospheric forcing at kilometer scales with light precipitation. J Geophys Res 106(C6):11399–11410

    Article  Google Scholar 

  • Liu S, Kermani A, Shen L, Yue D (2009) Investigation of coupled air–water turbulent boundary layers using direct numerical simulations. Phys Fluids 21:062108

    Article  Google Scholar 

  • Lombardi P, De Angelis V, Banerjee S (1996) Direct numerical simulation of near-interface turbulence in coupled gas–liquid flow. Phys Fluids 8(6):1643–1665

    Article  Google Scholar 

  • Manneville P (2006) Rayleigh–Bénard Convection: thirty years of experimental, theoretical, and modeling work. Dyn Spatio-Temporal Cell Struct Springer Tracts Mod Phys 207:41–65

    Article  Google Scholar 

  • Moeng C-H, Rotunno R (1990) Vertical-velocity skewness in the buoyancy-driven boundary layer. J Atmos Sci 47:1149–1162. doi:10.1175/1520-0469(1990) 047

    Article  Google Scholar 

  • Noh Y, Cheon WG, Raasch S (2003) The role of preconditioning in the evaluation of open-ocean deep convection. J Phys Oceanogr 33:1145–1166

    Article  Google Scholar 

  • Noh Y, Goh G, Raasch S (2010) Examination of the mixed layer deepening process during convection using LES. J Phys Oceanogr 40:2189–2195

    Article  Google Scholar 

  • Raasch S, Etling D (1998) Modeling deep ocean convection: large-eddy simulation in comparison with laboratory experiments. J Phys Oceanogr 28:1786–1802

    Article  Google Scholar 

  • Raasch S, Schröter M (2001) PALM—a large-eddy simulation model performing on massively parallel computers. Meteorol Z 10:363–372. doi:10.1127/0941-2948/2001/0010-0363

    Article  Google Scholar 

  • Rashidi M, Banerjee S (1990) The effect of boundary conditions and shear rate on streak formation and breakdown in turbulent channel flow. Phys Fluids A 2:1827–1838

    Article  Google Scholar 

  • Riechelmann T, Noh Y, Raasch S (2012) A new method for large-eddy simulations of clouds with Lagrangian droplets including the effects of turbulent collision. New J Phys 14:065008. doi:10.1088/1367-2630/14/6/065008

    Article  Google Scholar 

  • Saylor JR, Smith GB, Flack KA (2001) An experimental investigation of the surface temperature field during evaporative convection. Phys Fluids 13(2):428–439

    Article  Google Scholar 

  • Schiller A, Godfrey JS (2005) A diagnostic model of the diurnal cycle of sea surface temperature for use in coupled ocean–atmosphere models. J Geophys Res 110(C11):014. doi:10.1029/2005JC002975

    Google Scholar 

  • Schmidt H, Schumann U (1989) Coherent structure of the convective boundary layer derived from large-eddy simulations. J Fluid Mech 200:511–562

    Article  Google Scholar 

  • Scotti A (2010) Large eddy simulation in the ocean. Int J Comput Fluid Dyn 24(10):393–406. doi:10.1080/10618562.2010.522527

    Article  Google Scholar 

  • Shay TJ, Gregg MC (1986) Convectively driven turbulent mixing in the upper ocean. J Phys Oceanogr 16:1777–1798

    Article  Google Scholar 

  • Sikora TD, Young G (1993) Observations of planview flux patterns within convective structures of the marine atmospheric surface layer. Boundary-Layer Meteorol 65:273–288

    Article  Google Scholar 

  • Soloviev A, Lukas R (2006) The near-surface layer of the ocean: structure, dynamics and applications. Springer, Dordrecht, p 547

    Google Scholar 

  • Steinhorn I (1991) On the concept of evaporation from fresh and saline water bodies. Water Resour Res 27(4):645–648. doi:10.1029/90WR02759

    Article  Google Scholar 

  • Suhring M, Raasch S (2013) Heterogeneity-induced heat-flux patterns in the convective boundary layer: can they be detected from observations and is there a blending height?—a large-eddy simulation study for the LITFASS-2003 experiment. Boundary-Layer Meteorol 148:309–331. doi:10.1007/s10546-013-9822-1

    Article  Google Scholar 

  • Sullivan PP, McWilliams JC, Melville WK (2007) Surface gravity wave effects in the oceanic boundary layer: large-eddy simulation with vortex force and stochastic breakers. J Fluid Mech 593:405–452

    Article  Google Scholar 

  • Sullivan PP, Edson JB, Hristov T, McWilliams JC (2008) Large eddy simulations and observations of atmospheric marine boundary layers above non-equilibrium surface waves. J Atmos Sci 65:1225–1245

    Article  Google Scholar 

  • Sura P, Sardeshmukh PDS (2008) A global view of non-Gaussian SST variability. J Phys Oceanogr 38:639–647

    Article  Google Scholar 

  • Sura P, Sardeshmukh PDS (2009) A global view of air–sea thermal coupling and related non-Gaussian SST variability. Atmos Res 94(1):140–149

    Article  Google Scholar 

  • Trump CL, Neshyba SJ, Burt WV (1982) Effects of mesoscale atmospheric convection cells on the water of the East China Sea. Boundary-Layer Meteorol 24(1):15–34

    Article  Google Scholar 

  • Wickers LJ, Skamarock WC (2002) Time-splitting methods for elastic models using forward time schemes. Mon Weather Rev 130:2088–2097

    Article  Google Scholar 

  • Zilitinkevich SS, Hunt JCR, Grachev AA, Esau I, Lalas DP, Akylas E, Tombrou M, Fairall CW, Fernando HJS, Baklanov A, Joffre SM (2006) The influence of large convective eddies on the surface layer turbulence. Q J R Meteorol Soc 132:1423–1456

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the Norwegian Centre for Climate Dynamics (SKD), the Norway-Russia bilateral project CLIMARC and the European Research Council Advanced Grant PBL-PMES n227915. The author is grateful to Prof. S. Raash, Dr. B. Maronga, and Dr. M. Letzel for their help with the model development, set up, runs and discussions. The Norwegian Metacenter for Computational Science (NOTUR), accounts nn2343k and nn2993k, provided the computational infrastructure for this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Igor Esau.

Additional information

Responsible Editor: Richard John Greatbatch

This article is part of the Topical Collection on the 5th International Workshop on Modelling the Ocean (IWMO) in Bergen, Norway 17–20 June 2013

Rights and permissions

Reprints and permissions

About this article

Cite this article

Esau, I. Indirect air–sea interactions simulated with a coupled turbulence-resolving model. Ocean Dynamics 64, 689–705 (2014). https://doi.org/10.1007/s10236-014-0712-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10236-014-0712-y

Keywords

Navigation