Coupled Ocean-Atmosphere Interaction at Oceanic Mesoscales

Satellite observations have revealed a remarkably strong positive correlation between sea-surface temperature (SST) and surface winds on oceanic mesoscales of 10-1000 km. While this SST influence on the atmosphere had previously been identified from several in situ observational studies, its widespread existence in regions of strong SST gradients throughout the World Ocean and the detailed structure of the surface wind response to SST have only become evident over the past decade from simultaneous satellite measurements of SST and surface winds. This has stimulated considerable scientific interest in the implications of this air-sea interaction to the large-scale and mesoscale circulation of the atmosphere and ocean. Convergence and divergence of surface winds in regions of spatially varying SST generate vertical motion that can penetrate deep into the atmosphere. Spatial variability of the SST field also results in a curl of the wind stress and its associated upwelling and downwelling that feeds back on the ocean and alters the SST itself. Significant progress has been made toward

between sea surface temperature (SST) and surface winds on oceanic mesoscales of 10-1000 km.Although SST influence on the atmosphere had previously been identified from several in situ observational studies, its widespread existence in regions of strong SST gradients throughout the world's ocean and the detailed structure of the surface wind response to SST have only become evident over the past decade from simultaneous satellite measurements of SST and surface winds.This has stimulated considerable scientific interest in the implications of this air-sea interaction to large-scale and mesoscale circulation of the atmosphere and ocean.Convergence and divergence of surface winds in regions of spatially varying SST generate vertical motion that can penetrate deep into the atmosphere.Spatial variability of the SST field also results in a curl of the wind stress and associated upwelling and downwelling that feeds back on the ocean and alters SST itself.Significant progress has been made toward understanding the two-way coupling between the ocean and atmosphere but many exciting research opportunities remain.In addition to regional and global modeling, future research on coupled ocean-atmosphere interaction will continue to be guided by satellite observations.In particular, high-resolution measurements in the vicinity of narrow, intense SST fronts and immediately adjacent to land provided by the next-generation scatterometer will open up new areas of research that cannot be addressed from presently available data sets.
b y d u d l e y b .c h e lT o N a N d S h a N g -p I N g X I e The September 2004 average wind stress curl over the california current System constructed from QuikScaT measurements of surface wind stress.The positive (red) and negative (blue) areas correspond to regions of upwelling and downwelling, respectively, and are induced by crosswind gradients of the sea surface temperature field (see Figure 3 and the related text in this article).because of antenna sidelobe contamination, QuikScaT could not measure winds closer than about 30 km to land.The wind stress curl field shown here was extrapolated to the coast for visualization purposes.After Chelton et al., 2007

INTroducTIoN
The air-sea interface is of great interest (SST) and surface wind speed (Xie, 2004, and references therein).Except in the tropics, this interaction at large scales is interpreted as the ocean passively responding to wind-induced latent and sensible heat flux (i.e., a one-way forcing of the ocean by the atmosphere).
The advent of satellite-borne microwave radar scatterometers that measure the global surface wind field with a high spatial resolution of about 25 km, as described by Chelton and Freilich (2005), and microwave radiometers that measure SST in nearly all weather conditions with a spatial resolution of about 50 km, as described by Wentz et al. (2000) and Chelton and Wentz (2005), has revealed that ocean-atmosphere interaction is fundamentally different on oceanic mesoscales of 10-1000 km.Surface wind speed is found to be locally higher over warm water and lower over cool water (i.e., a positive correlation that is opposite to that found on large scales).
The fact that a positive correlation between SST and surface winds occurs only on small scales implies that associated ocean-atmosphere interaction is driven by spatial variations of SST.
TMI measurements of SST were used by Nonaka and Xie (2003)  dinate system that moves with the eddies and is orientated relative to the direction of the ambient wind (Park and Cornillon, 2002;Park et al., 2006).(Cornillon and Park, 2001;Kelly et al., 2001;Chelton et al., 2004;Park et al., 2006).

SurFace WINd reSpoNSe To SST
A paradoxical feature of the observed influence of SST on surface winds is that wind speed and wind stress magni- in low-wind conditions.For example, a 1 ms -1 increase in ambient winds of 10 ms -1 results in a stress increase that is about a factor of two larger than that from a 1 ms -1 increase for ambient winds of 5 ms -1 .
In addition to explaining why both  et al., 2001, 2004;O'Neill et al., 2003O'Neill et al., , 2005;;Larry O'Neill, Naval Research Laboratory, and colleagues, pers. comm., 2010).acceleration where winds blow across the SST front generates divergence (green area).lateral variations where winds blow parallel to the SST front generate curl (red area).The divergence and curl perturbations are proportional to the downwind and crosswind components of the SST gradient, respectively (see Figure 3).
Most analyses (Thiébaux et al., 2003).This change resulted in an abrupt increase in the intensity of wind speed variations on scales of 100-1000 km (Chelton, 2005;Chelton and Wentz, 2005;Maloney and Chelton, 2006;Song et al., 2009).coupled ocean-atmosphere models are too coarse to resolve mesoscale SST influence on surface winds.With sufficient grid resolution, however, the coupling becomes evident (Maloney and Chelton, 2006;Bryan et al., 2010).This

SST INFlueNce oN cloudS aNd TropoSpherIc WINdS
The preceding discussion has empha- The significance of this SST-induced upward motion is readily apparent in Figure 5c from the narrow band of heavy rain that has long been known to exist along the seaward side of the Gulf Stream (Hobbs, 1987).Consistent with coastal radar measurements of a sharp rise in echo height over the Gulf Stream (Trunk and Bosart 1990), this is also a region of enhanced lightning activity (Minobe et al., 2010).Models indicate that the surface wind convergence that anchors the deep upward motion  (Young and Sikora, 2003) and in the Agulhas Return Current region (Lutjeharms et al., 1986;O'Neill et al., 2005;Bryan et al., 2010).The influence of SST on clouds, both directly by its effects on vertical mixing and through its influence on divergence and convergence of surface winds and the associated vertical velocity field, is also evident on the small scales of Gulf Stream eddies (Park et al., 2006).et al. (2007) features in the ocean model simulation.
A better approach may therefore be to force ocean models with deliberately smooth wind stress fields and augment this smooth forcing with small-scale perturbations of the wind stress field determined from the model SST using empirical coupling by procedures such as those summarized above.
The ideal approach is to use fully coupled ocean-atmosphere models rather than ocean-only models forced by imposed wind stress fields.Although sufficient grid resolution to resolve the coupling on oceanic mesoscales is only beginning to become feasible with global coupled models (e.g., Bryan et al., 2010), this can readily be achieved with regional coupled models.Care must be taken, however, to assure that the coupling is accurately represented in the coupled models.The coupling intensity in models evidently depends on more than just model configuration since the model developed by Seo et al. (2007a) accurately represents the coupling in the TIW region but considerably underestimates the coupling in the CCS region.

Summary aNd coNcluSIoNS
The Vector Winds Mission (XOVWM) will enable studies of surface wind response to SST on scales nearly an order of magnitude smaller than can be resolved by QuikSCAT (Gaston and Rodrìguez, 2008;Rodrìguez et al., 2009).This will T h e F u T u r e o F o c e a N o g r a p h y F r o m S pa c e coupled oceaN-aTmoSphere INTeracTIoN aT oceaNIc meSoScaleS abSTr acT.Satellite observations have revealed a remarkably strong positive correlation to oceanographers and atmospheric scientists alike.Winds blowing across the sea surface are the primary forcing mechanism for ocean circulation.Winds also generate evaporative cooling of the sea surface, a major mechanism for the ocean to balance the radiative heat flux across the ocean surface.Water vapor released into the atmosphere by evaporation is mixed throughout the marine atmospheric boundary layer (the lowest 1-2 km of the atmosphere) and transported into the overlying troposphere that extends to a height of about 12 km.When this water vapor condenses to form clouds and precipitation, the associated release of latent heat is a source of energy driving atmospheric circulation.The coupled interaction between the ocean and the atmosphere at the sea surface is thus key to understanding both oceanic and atmospheric circulation, and is therefore critically important for weather forecasting and determining the roles of the ocean and atmosphere in climate variability.Most of what was known before the turn of this century about the space-time variability of winds over the ocean was based on reports from ships of opportunity.The sparse distribution of these observations restricted the resolution to scales larger than several hundred kilometers, and large areas outside of standard shipping routes were seldom sampled.Analyses of these coarseresolution ship observations in conjunction with coupled climate modeling on similarly coarse scales generally find a negative correlation between sea surface temperature presumably related to the equilibrium adjustment time of the marine atmospheric boundary layer and thus likely differs somewhat from one region to another, depending on the ambient wind speed and other factors.In regions of meandering SST fronts, mesoscale SST modifications of the surface wind field result in convergences and divergences of the surface winds and associated pressure perturbations that generate vertical motions that can penetrate into the troposphere, thus potentially influencing global weather patterns.SST-induced wind stress variations also feed back on the ocean surface in the form of wind-induced turbulent heat flux and mixing, as well as wind stress curl driven upwelling that generates ocean currents and can modify the SST itself.This article summarizes the progress in understanding the characteristics, physics, and significance of this two-way coupled ocean-atmosphere interaction on oceanic mesoscales.hISTorIcal backgrouNd High-resolution observational studies of the two-dimensional horizontal structure of mesoscale SST influence on low-level winds mandate the use of satellite measurements of winds and SST.To investigate an SST influence on surface winds hypothesized from an analysis of historical ship observations in the eastern tropical Pacific by Wallace et al. (1989) and from buoy observations in the same region by Hayes et al. (1989), Xie et al. (1998) conducted the first satellite-based study of the coupling between SST and surface winds using surface vector wind observations from the scatterometer on the European Remote Sensing satellite.They showed that surface wind divergence anomalies in the eastern tropical Pacific propagate westward at the same speed as the SST signatures of tropical instability waves (TIWs).The greatly improved sampling provided by the wide-swath QuikSCAT scatterometer that was launched in June 1999, in combination with all-weather microwave measurements of SST from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI; Wentz et al., 2000), facilitated numerous detailed investigations of the spacetime structure of the response of the surface wind field to TIW-induced SST variations in the eastern tropical Pacific to investigate the coupling between winds and SST on the southern flank of the Kuroshio Extension.Because of the low inclination of the TRMM orbit, however, TMI data are unable to provide the all-weather observations needed for detailed investigation of ocean-atmosphere interaction at latitudes higher than 38°.The availability of global microwave measurements of SST from the Advanced Microwave Scanning Radiometer (AMSR-E; Chelton and Wentz, 2005) on the Earth Observing System Aqua satellite beginning in June 2002 enabled the first detailed observational studies of mid-latitude ocean-atmosphere coupling at oceanic mesoscales.In the first such study, O'Neill et al. (2005) found a very strong positive correlation between QuikSCAT winds and SST measured by AMSR-E over the Agulhas Return Current in the Southwest Indian Ocean.As reviewed by Small et al. (2008), analyses of AMSR-E and QuikSCAT observations expanded rapidly thereafter.SST influence on surface winds has been found in every region of strong SST fronts investigated from these satellite observations.Moreover, Sampe and Xie (2007) found that extreme wind events occur much more frequently over the warm flanks of SST fronts in the North Atlantic and Southern Ocean.Coupling between the ocean and atmosphere at mid latitudes is most clearly seen by averaging over a few weeks or more (O'Neill et al., 2005; Chelton et al., 2007), which reduces the effects of energetic synoptic weather variability that often masks the comparatively subtle air-sea interaction.The persistence of the SST-induced small-scale features of the surface wind field in the vicinity of meandering SST fronts is on the order of a month or longer, controlled by the dynamical persistence of the current meanders.Similar persistence of the surface wind response to SST is evident over mesoscale ocean eddies when viewed in a rotating and translating coor- Figure 1.maps and binned scatter plots for two-month averages (January-February 2008) of spatially high-pass-filtered sea surface temperature (SST; which has zero mean, by definition) overlaid as contours on spatially high-pass-filtered wind stress magnitude for the agulhas return current region (left) and the gulf Stream region (right).(a) QuikScaT observations of wind stress and advanced microwave Scanning radiometer (amSr-e) observations of SST.(b) european centre for medium-range Weather Forecasts (ecmWF) wind stress and real-Time global (rTg) SST.(c) uS National centers for environmental prediction (Ncep) wind stress and reynolds SST.(d) Wind stress and SST from the National center for atmospheric research community climate System model (Ncar ccSm3.5)coupled climate model with atmosphere and ocean grid resolutions of 0.5° and 1.125°, respectively.(e) Wind stress and SST from the same Ncar ccSm3.5 coupled climate model with atmosphere and ocean grid resolutions of 0.5° and 0.1°, respectively.positive and negative high-pass filtered SST are shown as solid and dotted lines, respectively, with a contour interval of 1°c and with the zero contours omitted for clarity.The ccSm3.5 model simulations are not intended to represent actual years, so the two-month averages in panels d and e are for a representative January-February time period.The solid circles and error bars in the binned scatter plots are, respectively, the overall average and the standard deviation of the individual binned averages over eight January-February time periods for panels a-c and four January-February time periods for panels d and e.
tude are both linearly related to SST, despite the nonlinear relation between wind speed and wind stress.Larry O'Neill, Naval Research Laboratory, and colleagues (pers.comm., 2010) derived an analytical relationship that shows the wind stress magnitude on oceanic mesoscales is linearly proportional to the surface wind speed on the same scales with a proportionality factor that depends on the larger-scale ambient wind speed.This dependence on ambient winds is easily understood qualitatively because the change in wind stress is related to the square of the total wind speed, rather than to just the SST-induced perturbation wind speed.A given SST-induced wind-speed change thus results in a much greater change of wind stress in high-wind conditions than wind speed and wind stress are linearly related to SST, the dependence of the coupling on the ambient wind speed explains the observed larger temporal and geographical variations in the coupling coefficient between windstress magnitude and SST compared with that between wind speed and SST.The seasonal cycle serves as a good example of large temporal variations of the coupling.Because large-scale winds are stronger in winter in most regions, coupling between SST and wind stress is generally stronger in winter than in summer.The seasonal difference in coupling can be a factor of five over the Gulf Stream and Kuroshio Extension (Larry O'Neill, Naval Research Laboratory, and colleagues, pers.comm., 2010), where seasonal variations in the large-scale wind field are large.In the Southern Ocean where seasonal variability of large-scale winds is smaller, the coupling is only about a factor of two larger in winter than in summer.Seasonal variations in coupling imply a seasonal modulation of SST-induced wind stress curl feedback effects on ocean circulation; these effects are discussed in a later section.A consequence of SST influence on surface winds is that spatial variability of SST generates divergence and curl of the surface wind field (Figure 2).Divergence of surface wind and stress are both found to be linear functions of the downwind component of the SST gradient; the curl of surface wind and stress are likewise both found to be linear functions of the crosswind component of the SST gradient (Chelton Figure 3 shows these relations for wind stress divergence and curl in the Agulhas Return Current and Gulf Stream regions.It is visually apparent that the correlations between the curl fields and crosswind SST gradients are consistently smaller than correlations between the divergence fields and downwind SST gradients (e.g., Figure 3).This is due in part to the above-noted effects of ocean surface currents, which affect wind stress curl and relative wind vorticity measured by scatterometers, but have very little effect on wind and stress divergence because ocean currents are nearly nondivergent.Surface ocean currents therefore have a negligible effect on wind stress divergence and relative

Figure 2 .
Figure2.Schematic illustration of the divergence and curl of the wind and wind stress fields that result from spatial variations of the SST field.Near a meandering SST front (the heavy black line), surface winds are lower over cool water and higher over warm water, shown qualitatively by the lengths of the vectors.acceleration where winds blow across the SST front generates divergence (green area).lateral variations where winds blow parallel to the SST front generate curl (red area).The divergence and curl perturbations are proportional to the downwind and crosswind components of the SST gradient, respectively (see Figure3).
studies of the divergence and curl responses of surface winds to downwind and crosswind SST gradients have focused on regions of strong SST fronts associated with meandering currents.Park and Cornillon (2006) showed that divergence and curl of surface winds also develop over Gulf Stream eddies in association with SST distribution in the interiors of the eddies.The divergence and curl responses to spatially varying SST have important implications for both the atmosphere and the ocean.In the case of the atmosphere, SST influence can penetrate into the troposphere from the vertical motion induced by convergence and divergence of the surface wind field.In the case of the ocean, the upwelling and downwelling that are associated with the wind stress curl alter the ocean circulation, and therefore the SST itself.Another paradoxical feature of the observed air-sea interaction is that the coupling coefficients between the wind stress divergence and the downwind SST gradient are consistently larger than those between the wind stress curl and the crosswind SST gradient (Figure 3), and likewise for vector wind divergence and vorticity.By explicitly relating wind divergence and vorticity to crosswind and downwind gradients of wind speed and direction using natural coordinates defined by the wind direction, O'Neill et al. (2010a) showed that wind speed gradients contribute equally to the curl and divergence responses to SST.The differences between the curl and divergence responses are thus attributable to the effects of SST on wind direction.SST-induced crosswind and downwind gradients in wind direction reduce the curl response to crosswind SST gradients through rotation while simultaneously enhancing the divergence response to downwind SST gradients through confluence and difluence.SST-induced surface pressure gradients play an important role in this wind directional dependence on SST.SST INFlueNce IN NumerIcal WeaTher predIcTIoN aNd coupled clImaTe modelSA question of great interest to weather forecasters, and to researchers using atmospheric models for studies of climate variability or to force ocean circulation models, is the degree to which the observed SST influence on surface winds is reproduced in models.For grid resolutions that are used in present-day numerical weather prediction (NWP) models, this depends sensitively on the resolution of the SST fields that are used for the surface boundary condition in the models.This is readily apparent in the wind fields from the European Centre for Mediumrange Weather Forecasts (ECMWF) operational NWP model.In May 2001, the SST boundary condition in the ECMWF model was changed from the low-resolution Reynolds SST analyses(Reynolds et al., 2002) to the higherresolution Real-Time Global (RTG) SST

Further
Figure 1b, however, that this small-scale variability is about a factor of two weaker than in the QuikSCAT observations in Figure 1a.The underestimation of wind stress curl and divergence in the difference can be seen by comparing SST and surface wind stress fields from two runs of version 3.5 of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM3.5;Bryan et al., 2010).With a grid resolution of 0.5° for the atmosphere model and a coarse grid resolution of 1.125° for the ocean model, a positive correlation between SST and wind stress is visually apparent, but with spatial scales that are grossly too large (Figure 1d).When the ocean grid resolution is increased to 0.1°, the coupled patterns of SST and wind stress are clearly defined and much smaller in scale (Figure 1e).Although the resolution of the SST boundary condition, or the grid resolution of the ocean model in the case of coupled models, is critically important to atmospheric model representations of SST-induced variability in the surface wind field on oceanic mesoscales, it is not the only factor limiting the accuracies of atmospheric models.The oceanatmosphere coupling in these models can be quantified by the slope of the linear relation between SST and surface wind speed or wind stress.As the binned scatter plots in Figure 1 show, coupling is smaller than the observed coupling by a factor of two to four for all of the NWP and climate models considered here.Thus, even if a perfect SST boundary condition were used for these models, they would underestimate the surface wind and stress responses.The underrepresentation of surface wind response to SST in the ECMWF model was investigated in detail from sensitivity studies conducted with the Weather Research and Forecasting (WRF) mesoscale atmospheric model for the Agulhas Return Current region (Song et al., 2009).The conclusions of this study are likely relevant also to the NCEP model and the CCSM3.5 coupled models considered above, as well as to most other atmospheric models.Aside from the importance of the resolution of the SST boundary condition discussed above, the primary factor limiting the accuracy of the coupling appears to be the parameterization of vertical mixing.When configured with horizontal and vertical grid resolutions comparable to those in the ECMWF model and with the Mellor and Yamada (1982) parameterization of vertical mixing, the WRF model accurately reproduces the ECMWF surface wind response to SST (Figure 4a,b), which is about a factor of two weaker than the coupling deduced from the satellite observations.When the sensitivity of the Mellor-Yamada mixing to atmospheric stability is increased by a factor of five as recommended by Grenier and Bretherton (2001), the observed surface wind response to SST in the QuikSCAT observations is accurately represented in the WRF model (Figure 4c,d).The sensitivity of vertical mixing to SST-induced variations in the stability of the boundary layer thus appears to be too weak by about a factor of five in the parameterization used in the ECMWF model.This results in underestimation by about a factor of two in surface wind response to SST.In addition to the details of the parameterization of vertical mixing, the degree of underestimation of the coupling between SST and surface winds in models likely depends also on the models' vertical grid resolution.For example, the atmosphere component of the US Navy Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS) of wind response to SST over the California Current System considered by Haack et al. (2008) underestimates the surface wind response to SST by only about 20%, despite the use of the Mellor and Yamada (1982) mixing parameterization.Their configuration of the COAMPS model has 15 grid points in the boundary layer, compared with 11 grid points in the WRF model summarized above.In the COAMPS model configured by Perlin et al. (2007) to use the Mellor and Yamada (1982) mixing parameterization with 31 grid points in the boundary layer, there was no apparent underestimation of the surface wind response to SST.The underrepresentation of the SST influence on surface winds in most atmospheric models has two important implications.First, since the surface wind response to SST is underestimated, any tropospheric response to SST will also be underestimated.The influence of this ocean-atmosphere interaction on the general circulation of the atmosphere may therefore be considerably misrepresented in present NWP and coupled climate models.Second, ocean models forced with the surface winds from NWP models, or coupled to similar atmospheric models, will underestimate any feedback effects that SST-induced small-scale wind forcing may have on ocean circulation.These two issues are addressed further in the next two sections.
Figure 4. monthly averages for July 2002 of spatially high-pass-filtered SST (contours in all panels) and (a) 10-m wind speed from the ecmWF operational model, (b) 10-m wind speed from the WrF model with mellor and yamada (1982) parameterization of vertical mixing, (c) 10-m equivalent neutral wind speed from QuikScaT observations, and (d) 10-m equivalent neutral wind speed from the WrF model with grener and bretherton (2001) parameterization of vertical mixing.SST is from rTg in panels a and b and from amSr-e in panels c and d. positive and negative high-pass-filtered SSTs are shown as solid and dotted lines, respectively, with a contour interval of 1°c and with the zero contours omitted for clarity.Modified fromSong et al. (2009)

Figure 5 .
Figure 5. annual means of (a) surface wind convergence from QuikScaT observations of surface winds, (b) vertical velocity in pressure coordinates from the ecmWF model, (c) rain rate from the Tropical rainfall measuring mission satellite observations, and (d) upper-tropospheric divergence from the ecmWF model averaged over the pressure range 500-200 hpa.The contours in panels a, c, and d show SST with a contour interval of 2°c.The black line in panel b is the boundary layer height, and the other contours plot wind convergence averaged in the along-front direction across the green box in panel d with a contour interval of 10 -6 s -1 (solid for convergence and dashed for divergence, with the zero contours omitted for clarity).Modified fromMinobe et al. (2008) schemes.Pezzi et al. (2004) considered an ocean model of TIWs in the Pacific Ocean forced with steady, large-scale winds that were augmented by smallscale perturbations that were linearly related to the model SST anomalies based on coupling coefficients estimated from QuikSCAT observations.This two-way empirical coupling resulted in a modest (~10%) but significant negative discovery of the ubiquity of the covariability between mesoscale features in the SST field and surface winds in regions of strong SST fronts throughout the world's ocean is one of the significant successes of satellite remote sensing of the ocean.Satellite observations have enabled rapid progress in the understanding of this mesoscale coupled ocean-atmosphere interaction over the past decade.The details of the influence of SST on surface winds have been thoroughly documented from simultaneous measurements of surface winds by the QuikSCAT scatterometer and satellite measurements of SST.Early studies of SST influence on surface winds used infrared measurements of SST, which are available only during clear-sky conditions (e.g.,Xie et al., 1998).The regions where this air-sea interaction occurs are frequently cloud covered.Indeed, as discussed earlier, this air-sea interaction often generates clouds near SST fronts.Since the advent of all-weather SST measurements (except in rainy conditions) by the microwave TMI and AMSR-E, nearly all observational studies of this phenomenon have been based on microwave observations.(Notable exceptions includePark and Cornillon, 2002;Park et al., 2006;and Song et al., 2006.)The ability to measure SST through clouds generally outweighs the resolution limitations of the coarse footprint size of about 50 km for microwave observations, particularly for coupled SSTwinds, they are not sufficient to understand all of the physical processes involved in this air-sea interaction.The dynamics and thermodynamics of this coupling have been elucidated from analytical and numerical modeling studies.The satellite observations are crucially important for validating these models.In ongoing research, the satellite observations of ocean-atmosphere coupling are also providing important metrics for assessment of global numerical weather prediction models and coupled climate models.In the case of NWP models, the surface wind response to SST is strongly dependent on the spatial resolution of the SST boundary condition.Analogously, model grid resolution is critically important for the ocean component of coupled models.Satellite observations have also drawn attention to the importance of the parameterization of vertical mixing in models, most of which appear to underestimate the sensitivity of mixing to atmospheric stability.These satellite observations also offer robust benchmarks for validating and improving surface winds and low-level clouds in coupled climate models.SST influence on surface winds has stimulated exciting research opportunities in atmospheric sciences.The significance of mesoscale SST influence on the troposphere is only beginning to be explored.It is clear from the studies " …FuTure reSearch oN coupled oceaN- aTmoSphere INTeracTIoN WIll coNTINue To be guIded by SaTellITe obSerVaTIoNS." conducted to date, however, that the coupling between SST and the troposphere can be strong and may therefore be important to the large-scale circulation of the atmosphere.Investigations of the dynamical response of the troposphere to SST-induced perturbations of winds in the boundary layer have thus far relied on models of tropospheric winds.Because most models underestimate the surface wind response to SST, they likely also underestimate the tropospheric response.Understanding the importance of SST to the large-scale circulation of the atmosphere therefore requires improvements in the models.Observational studies will likely also be critically important to understanding the SST influence on the troposphere.In particular, satellite measurements of vertical profiles of atmospheric temperature, humidity, clouds, and precipitation can provide detailed information about the vertical structure of tropospheric response to SST on oceanic mesoscales.Satellite observations have also stimulated exciting research opportunities in oceanography.The significance of the feedback effects of SST-induced Ekman pumping anomalies on ocean circulation and on SST itself are also only beginning to be explored.While most of the modeling studies conducted to date have been very idealized, they show that the two-way coupling can have a strong influence on ocean circulation.This is motivating the development of both regional and global coupled models, which may become the norm for ocean modeling in the not-too-distant future.The two-way coupling is likely also important to marine ecosystem dynamics through the Ekman pumping of nutrients into or out of the euphotic zone where they are needed for primary production by phytoplankton.This could have important ramifications for the global carbon budget.The satellite observations of covariability of SST and surface winds on oceanic mesoscales are thus providing the impetus for a wide variety of atmospheric and oceanographic research.Rapid progress in understanding of the wide-ranging importance of this oceanatmosphere coupling can be expected in the coming years.Satellite measurements of SST and ocean surface vector winds will continue to play a vital role in this research.As noted above, satellite measurements of vertical profiles of temperature, humidity, clouds, and precipitation will provide important new information on SST's influence on the troposphere.In addition, the next-generation synthetic aperture radar (SAR) scatterometer called the Extended Ocean spatial resolution, XOVWM will provide high-resolution measurements of winds immediately adjacent to land where the wind field is influenced by a complex combination of processes that includes the effects of SST discussed here as well as orographic effects of land on air flow and the influence of diurnal and seasonally varying sea-breeze effects from daytime and summer heating over land.This will open up altogether new research on coastal meteorology that cannot be addressed from present scatterometer technology.ackNoWledgmeNTS We thank Frank Bryan and Bob Tomas for providing the output from the NCAR CCSM3.5 model shown in Figure 1, Qingtao Song for the model wind fields shown in Figure 4, Shoshiro Minobe for providing Figure 5, Natalie Perlin for providing Figure 6, and Michael Schlax for generating all of the final figures for this paper.We also thank Ralph Milliff, Peter Cornillon, and Larry O'Neill for helpful comments on the original manuscript.The authors gratefully acknowledge NASA support for Ocean Vector Winds Science Team activities.This is IPRC/SOEST publication #719/8010.reFereNceS Bryan, F.O., R. 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