diurnal sea surface temperature variation and its im- pact ... · journal of oceanography, vol. 63,...

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Journal of Oceanography, Vol. 63, pp. 721 to 744, 2007

Review

Keywords:⋅⋅⋅⋅⋅ Sea surfacetemperature,

⋅⋅⋅⋅⋅ diurnal variation,⋅⋅⋅⋅⋅ intraseasonalvariation,

⋅⋅⋅⋅⋅ air-sea interaction,⋅⋅⋅⋅⋅ surface flux.

* Corresponding author. E-mail: [email protected]

Copyright©The Oceanographic Society of Japan/TERRAPUB/Springer

Diurnal Sea Surface Temperature Variation and Its Im-pact on the Atmosphere and Ocean: A Review

YOSHIMI KAWAI1* and AKIYOSHI WADA2

1Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, Natsushima-cho, Yokosuka 237-0061, Japan2Meteorological Research Institute, Japan Meteorological Agency, Nagamine, Tsukuba 305-0052, Japan

(Received 6 November 2006; in revised form 2 April 2007; accepted 14 April 2007)

The importance of the diurnal variability of sea surface temperature (SST) on air-seainteraction is now being increasingly recognized. This review synthesizes knowledgeof the diurnal SST variation, mainly paying attention to its impact on the atmosphereor the ocean. Diurnal SST warming becomes evident when the surface wind is weakand insolation is strong. Recent observations using satellite data and advanced in-struments have revealed that a large diurnal SST rise occurs over wide areas in aspecific season, and in an extreme case the diurnal amplitude of SST exceeds 5 K. Thelarge diurnal SST rise can lead to an increase in net surface heat flux from the oceanof 50–60 Wm–2 in the daytime. The temporal mean of the increase exceeds 10 Wm–2,which will be non-negligible for the atmosphere. A few numerical experiments haveindicated that the diurnal SST variation can modify atmospheric properties over thePacific warm pool or a coastal sea, but the processes underlying the modificationhave not yet been investigated in detail. Furthermore, it has been shown that thediurnal change of ocean mixing process near the surface must be considered cor-rectly in order to reproduce SST variations on an intraseasonal scale in a numericalmodel. The variation of mixed-layer properties on the daily scale is nonlinearly re-lated to the intraseasonal variability. The mixed-layer deepening/shoaling process onthe daily scale will also be related to biological and material circulation processes.

(e.g., Reynolds et al., 2002; Rayner et al., 2003; Worleyet al., 2005). Although these high-quality datasets enableus to investigate long-term and large-scale variations, thespatial and temporal resolution of these SST data is toopoor to resolve eddies and temporal high-frequency vari-ation. Several researchers have shown that the imposi-tion of an hourly surface forcing is essential to reproducediurnal and intraseasonal SST variations in a numericalmodel (e.g., Weller and Anderson, 1996; Sui et al., 1997b;Shinoda and Hendon, 1998; Bernie et al., 2005). Further-more, Li et al. (2001) and Clayson and Chen (2002) indi-cated that the diurnal SST variation can have an impacton the atmosphere over the western Pacific warm pool.The air-sea interaction on the daily scale may play animportant role in the Madden-Julian Oscillation (MJO),and in turn the El Niño and Southern Oscillation (ENSO)and climate (cf. Slingo et al., 2003; Dai and Trenberth,2004).

1. IntroductionSea surface temperature (SST) is the most important

factor in air-sea interaction. The sea surface is the lowerboundary of the atmosphere, and SST influences weatherand climate. On the other hand, SST is also controlled byatmospheric conditions. Accurate SST data are indispen-sable for climate monitoring, prediction and research. SSTis also important in chemical and biological oceanogra-phy. In order to clarify the mechanism of the global cli-mate system we need a high-quality SST dataset andknowledge of air-sea interaction processes.

SST data have been collected for more than a cen-tury, and form the most abundant dataset in oceanogra-phy. Nowadays several in situ or analytical long-term glo-bal SST datasets are produced and released to the public

722 Y. Kawai and A. Wada

Diurnal variation, which is caused by solar radiationand the earth’s rotation, is one of the dominant variationsin SST. The existence of the diurnal variation in SST wasknown at least one century ago (cf. Sverdrup et al., 1942;Roll, 1965). Sverdrup et al. (1942) indicated that “thediurnal variation of sea temperature in general is so smallthat it is of little importance to physical and biologicalprocesses in the sea, but knowledge of the small varia-tions is essential to the study of the diurnal exchange ofheat between the atmosphere and the sea.” The diurnalamplitude of SST is O (0.1 K) on average, but oftenreaches a few degrees and can exceed 5 K in extremecases (e.g., Flament et al., 1994; Yokoyama et al., 1995).The satellite remote sensing community has clearly rec-ognized that the diurnal SST variability has to be ad-equately considered to provide better accuracy of satel-lite-derived SST (e.g., Hepplewhite, 1989; Wick et al.,2002; Donlon and the GHRSST-PP Science Team, 2005;Notarstefano et al., 2006). However, the diurnal varia-tion has often been neglected in analytical SST datasetsor numerical modeling, and the effects of air-sea interac-tion on the daily scale have not yet been widely recog-nized nor adequately revealed.

Many researchers have recently become interestedin the diurnal SST variation, and increasing numbers ofstudies pay attention to air-sea interaction on the dailyscale. This review synthesizes knowledge of the diurnalSST variation, focusing on why and how the diurnal vari-ation is important for the atmosphere and the ocean.Soloviev and Lukas (2006) gave a detailed, comprehen-sive account of the structure and dynamics of the near-surface ocean. Furthermore, previous studies of the skineffect (see Section 2) were reviewed or introduced byKatsaros (1980), Robinson et al. (1984), and Ward et al.(2004a), for example. In this paper we focus on the diur-nal sea surface warming and its effect on the atmosphere,with less emphasis on the skin effect. We do not take upthe diurnal variation caused by the tide here.

First, the vertical temperature structure near the sur-face and the definition of SST are explained in Section 2.Section 3 summarizes previous observational studies thatshowed large diurnal variations in SST. Section 4 intro-duces several models used to simulate the diurnal SSTvariation. Sections 5 and 6 discuss how the diurnal vari-ability of SST affects the surface flux estimation and theatmosphere. Some main issues on modeling and observa-tion of the diurnal SST variation are mentioned in Sec-tion 7. The paper is summarized in Section 8.

2. Vertical Thermal Structure near the Sea Surfaceand SST TerminologyUnder clear and calm conditions, thermal stratifica-

tion is formed within the top few meters of the ocean dueto strong insolation. This diurnal stratified layer is often

called “the warm layer” (Fairall et al., 1996). Thethermocline near the surface that develops only in thedaytime is referred to as “diurnal thermocline”. Further-more, at the top of the ocean, a very thin cool layer, whichis usually called the “thermal skin layer”, “cool skin layer”or simply “skin layer”, almost always exists (e.g.,Saunders, 1967; Katsaros, 1980; Robinson et al., 1984;Ward and Donelan, 2006). The thickness of this layer isusually the order of 0.1–1 mm, and the temperature at thetop of the skin layer is generally several tenths of a de-gree colder than the temperature below it because eddydiffusion becomes less than molecular diffusion just closeto the surface. The phenomenon of the temperature dropoccurring in this thin layer is called the “skin effect”.While the diurnal thermocline vanishes by sunrise nextmorning, the skin layer usually exists in both the daytimeand nighttime, even in windy conditions (Donlon et al.,2002). In the daytime, the temperature difference acrossthe skin layer becomes smaller due to the absorption ofshortwave radiation in this layer. The temperature at thetop can theoretically even become higher than that at thebottom when the air temperature is very much higher thanthat of the water, as has been confirmed by a tank experi-ment (Ward and Donelan, 2006). The skin layer thick-ness and the diurnal thermocline depth vary with surfaceheat and momentum fluxes (e.g., Fairall et al., 1996; Wardand Donelan, 2006). A better knowledge of SST demandsconsideration of both the diurnal warming near the sur-face and the effect of the skin layer.

A sharp temperature gradient sometimes appearsabove 1-m depth in the daytime (e.g., Yokoyama et al.,1995; Soloviev and Lukas, 1997; Ward, 2006; see Figs.1–3 in the present paper). The large temperature differ-ence between the sea surface and about 1-m depth, whereships and buoys usually measure the seawater tempera-ture as “SST”, has been recognized as one of the majorsources of error in satellite-derived SST. The satellite in-frared sensor, microwave sensor, and in situ sensors ob-serve “different sea surfaces”, i.e., skin, subskin, and adepth of one or a few meters, respectively. Hence it wasindispensable to define SST exactly and consider carefultreatment of different SSTs when producing an accurateSST dataset. The Global Ocean Data Assimilation Ex-periment (GODAE) High-Resolution SST Pilot Project(GHRSST-PP) Science Team has been doing work oncoordinating a new generation of global, multi-sensor,high-resolution SST products for the benefit of the op-erational and scientific community (Donlon et al., 2007).

This Science Team has defined five kinds of SST:interface SST (SSTint), skin SST (SSTskin), subskin SST(SSTsubskin), sea temperature at depth (SSTdepth), and foun-dation SST (SSTfnd) (Donlon and the GHRSST-PP Sci-ence Team, 2005). A schematic picture of the vertical tem-perature profile is shown in Fig. 1, and the definitions of

Diurnal SST Variation and Its Impact 723

Name Abbreviation Temperature represented Instrument to measure it

Interface SST SSTint Theoretical temperature at the precise air-seainterface

None

Skin SST SSTskin Temperature within the conductive diffusion-dominated sub-layer at a depth ofapproximately 10−20 µm

Infrared radiometer operating in the 3.7−12

micrometer spectral waveband

Subskin SST SSTsubskin Temperature at the base of the conductive laminarsub-layer

Microwave radiometer operating in the 6−11 GHz

frequency range, high-performance autonomousprofiler (SkinDeEP, Ward et al., 2004b)

Sea temperature at depth SSTdepth In situ temperature measured below theconductive laminar sub-layer, which is

Traditional in situ sensor (thermistor, CTD, XBT,etc.)

Foundation SST SSTfnd Temperature of the water column free of diurnaltemperature variability or equal to the SSTsubskin

in the absence of any diurnal signal

″

Table 1. Definitions of the five kinds of SST proposed by Donlon and the GHRSST-PP Science Team (2005) and Donlon et al.(2007). See also Fig. 1.

the SSTs are explained in Table 1. In actuality, we cannotknow SSTint even with current technology (Donlon et al.,2002), and SSTskin is usually utilized as a substitute forSSTint on the assumption that SSTskin is close enough tothe true SSTint. The in situ SST measured at about 1-mdepth or deeper has been called “bulk” SST. The ScienceTeam recommends using “SSTdepth” rather than the con-ventional term “bulk SST” referring to an in situ SSTmeasurement made at 1-m depth as SST1m, for example.This terminology is introduced to encourage reporting ofthe measurement depth along with the temperature, be-cause, as depicted in Fig. 1, the temperature can changedrastically with depth when the diurnal thermocline isformed. The new concept of “foundation SST” is intro-duced as a more precise, well-defined quantity instead ofprevious, loosely-defined “bulk” SST, which is affectedby the diurnal warming. SSTfnd will be similar to anighttime minimum or pre-dawn value at depths of ~1–5m, but note that this depth is only a rough estimate andcan deviate from this range in some cases. This paperbasically adopts the terminology proposed by Donlon andthe GHRSST-PP Science Team (2005). When referringto the temperature near the surface in a general sense,loosely, the authors simply use “SST”.

While a satellite sensor sees SSTskin or SSTsubskin, insitu SST observed from ships and buoys is the tempera-ture at about 1-m depth or deeper. Algorithms of satel-lite-derived SST are conventionally tuned by using buoy-observed SST, i.e., SSTdepth, as the truth. Hence the aver-age of the satellite SST agrees with that of SSTdepth. How-ever, it is expected that the variability of the satellite SSTreflects that of SSTskin or SSTsubskin, rather than SSTdepth(cf. Kearns et al., 2000; Kilpatrick et al., 2001; Wick etal., 2002; Stuart-Menteth et al., 2003; Dong et al., 2006).Some researchers call such satellite SST “pseudo-bulk

SST” (Notarstefano et al., 2006). We should note that thesatellite SST tuned against SSTdepth has the above char-acteristics. For the recent satellite SST products from theAlong Track Scanning Radiometer (ATSR) (Mutlow etal., 1994) and the Tropical Rainfall Measurement Mis-sion (TRMM) satellite’s Microwave Imager (TMI)(Gentemann et al., 2004), the algorithms were developedbased on the radiance simulated by a radiative transfermodel in order to derive SSTskin or SSTsubskin exactly.

The atmosphere senses only the exact interface be-tween the atmosphere and the ocean. Hence we have toknow SSTint (or SSTskin practically) and its diurnal varia-tion for accurate estimation of air-sea heat and gas fluxes(e.g., Sarmiento and Sundquist, 1992; Fairall et al., 1996).If the temperature at a few meters depth is used as SSTintin a flux calculation, the atmosphere will receive incor-rect heat and water vapor from the ocean. This impact isnot always negligible, as discussed in Sections 5 and 6.

3. Observational Facts Concerning Diurnal SSTVariation—When and How can the Diurnal Vari-ation Become Large?

3.1 In situ observationSverdrup et al. (1942) and Roll (1965) introduced

some early observational studies of diurnal SST varia-tion. These early studies used research vessel SST data,which correspond to SSTdepth, and the depths of the meas-urements were not mentioned. For example, according tothem, a 1923 report based on data of German and Britishresearch vessels obtained during 1872–1903 stated thatmean diurnal amplitude of SST in the low latitude wasabout 0.3–0.4 K, and the amplitude decreased to 0.26 Kat 45–55°S and 0.15 K at 55–60°S. Koizumi (1956)analyzed ocean station data at Extra (39°N, 153°E) and


Tango (29°N, 135°E) in the northwestern Pacific. Heshowed that the diurnal amplitude of SST was smallest(0.15 K at Extra and 0.36 K at Tango) in winter and larg-est in summer (0.52 K at Extra and 0.65 K at Tango) on amonthly average. Koizumi (1956) also indicated that insummer the daily maximum occurred later (1500 LST)than in winter (around 1300 LST), although theseasonality of the time of the daily minimum was notobvious. Stommel and Woodcock (1951) and Stommel etal. (1969) reported examples of large diurnal SST risereaching 1–1.5 K in the Gulf of Mexico and south of Ber-muda in spring.

As mentioned above, in the early and mid twentiethcentury it was indicated that the diurnal amplitude of SSTwas about 0.2–0.6 K on average, varying with latitudeand season. It was also known that the diurnal amplitudedepended on cloudiness and wind speed, and could reachabout 1.5 K on clear, calm days. Stronger winds inducestronger turbulent mixing in the ocean and prevent ther-mal stratification. Furthermore, stronger turbulence in theatmosphere draws heat from the ocean. These two func-tions mean that the diurnal amplitude of SST decreasesas the wind becomes stronger. On the other hand, strongerinsolation causes a greater diurnal SST rise due to theabsorption of radiation near the sea surface. About 60%of incoming shortwave radiation is absorbed within theupper 1 m of the ocean (cf. Soloviev and Lukas, 2006).

In relatively recent years, larger diurnal SST varia-tions have been reported, using advanced instruments.Bruce and Firing (1974) showed an example of a diurnaltemperature rise exceeding 3 K in the layer of 0~1-mdepth, using slow-sinking Expendable Bathythermograph(XBT) probes. Other researchers also observed diurnalamplitudes of SSTdepth or SSTskin reaching 2–3 K or moreunder calm and clear conditions with buoys, profilingfloats, and infrared radiometers on vessels (e.g., Price etal., 1986, 1987; Yokoyama et al., 1995; Weller andAnderson, 1996; Webster et al., 1996; Soloviev and Lukas,1997; Kawai and Kawamura, 2002; Ward, 2006). In par-ticular, diurnal SST variations were minutely observedin the Pacific warm pool during the Tropical Ocean Glo-bal Atmosphere (TOGA)/Coupled Ocean-AtmosphereResponse Experiment (COARE) (cf. Godfrey et al., 1998).For example, Soloviev and Lukas (1997) observed manydiurnal thermocline profiles using a special instrumentcalled a free-rising profiler during COARE (Fig. 2). Thedepth of the diurnal thermocline tends to be shallower asthe gradient of the thermocline increases, and the forma-tion of a very sharp diurnal thermocline is restricted within0~1-m depth. Ward (2006) also showed temperature strati-fication of up to 2.7 K formed above 1-m depth using anautonomous profiling float called the “Skin Depth Ex-perimental Profiler (SkinDeEP)” (Fig. 3). This large tem-perature difference across the warm layer has a non-neg-

ligible influence on air-sea heat flux estimation (see Sub-section 5.1). According to the results of Soloviev andLukas (1997) and Donlon et al. (2002), the diurnalthermocline almost disappears when wind speed exceedsabout 5 m s–1. Furthermore, Webster et al. (1996) andSoloviev and Lukas (1997) indicated that the shallowhalocline caused by precipitation also affects the diurnalSST variation.

Infrared radiometers are sometimes operated on re-search vessels or an oil derrick to measure SSTskin (e.g.,Schlüessel et al., 1987, 1990; Fairall et al., 1996; Donlonet al., 1998; Kearns et al., 2000; Barton et al., 2004; Niclòset al., 2004). SSTskin is now urgently required for satel-lite SST tuning/validation and the study of air-sea fluxesand interaction, rather than SSTdepth. SSTskin shows largerdiurnal variations than SSTdepth under calm and clear con-ditions (e.g., Fairall et al., 1996; Donlon et al., 1998;Clayson and Chen, 2002). During windy conditions, thevariation of SSTskin is almost the same as that of SSTdepth,and SSTskin is a little cooler than SSTdepth and SSTsubskindue to the skin effect and the absence of the diurnalthermocline.

Several kinds of infrared radiometer for in situSSTskin observations have been developed, such as M-AERI, ISAR, SISTeR, CIRIMS, etc. (cf. Barton et al.,2004). However, infrared radiometers that can measureSSTskin with high accuracy are generally so expensive andcomplicated that the radiometric SST observations arenow restricting their usage to a limited number of researchvessel cruises. Wide spread usage of tough, low-cost ra-diometers will be also necessary (cf. Donlon et al., 1998).

3.2 Satellite observationOperational satellite SST observations started in the

1980s, and have provided the ability to investigate diur-nal SST variation over a wide region. Deschamps andFrouin (1984) studied the diurnal heating of the sea sur-face in the Mediterranean Sea using the SST observed bythe Heat Capacity Mapping Radiometer (HCMR) satel-lite. They indicated that the day-night SST differenceclearly depended on wind speed, and exceeded 3 K invery calm cases. Cornillon and Stramma (1985) andStramma et al. (1986) used the SST derived from theNational Oceanic and Atmospheric Administration(NOAA) satellite/Advanced Very High Resolution Radi-ometer (AVHRR) observation to show that the SST oftenbecame much higher in the daytime than the nighttime inthe northern Atlantic. The large diurnal warming occurredaround the ridge of the Azores-Bermuda high pressure inspring and summer, and the maximum day-night differ-ence reached 3–4 K. Flament et al. (1994) reported anexample of diurnal SST amplitude reaching 6.6 K locallyoff California using the AVHRR SST. Diurnal SST varia-tion is also affected by biological process, and it can be


detected by satellite observation. Kahru et al. (1993) re-ported that the AVHRR SST increased locally by up to1.5 K in the daytime in the southern Baltic Sea, corre-sponding to surface accumulations of cyanobacteria.

Large diurnal SST variations also frequently occurin the marginal seas around Japan from spring to summer(Yokoyama et al., 1995; Kawai and Kawamura, 1997,2000, 2002; Kawai et al., 2006a). Figure 4 shows an ex-ample of the extremely large SST difference between

morning and afternoon in the Japan Sea. The regionalsatellite SST dataset produced by Sakaida et al. (2000)was used here. In this case the diurnal SST rise exceeded3 K off the coast of northern Japan, and clearly corre-sponded to the weak wind. In the Japan Sea the diurnalwarming often becomes quite large under a ridge of highpressure or behind the high mountains of Japan.

Stuart-Menteth et al. (2003) first showed the globalclimatological distribution of the day-night SST differ-ence using six years of AVHRR SST data (see their fig-ure 9). From spring to summer the difference becomeslarger in the Mediterranean Sea, the Bay of Bengal, the

Fig. 1. Schematic showing (a) idealized nighttime vertical tem-perature deviations from the foundation SST and (b) ideal-ized daytime vertical temperature deviations from the foun-dation SST in the upper ocean. From Donlon and theGHRSST-PP Science Team (2005). Courtesy of C. J.Donlon.

Fig. 2. Vertical temperature profiles in the TOGA COARE do-main obtained by a free-rising profiler during different windspeed conditions taken at approximately the same afternoontime on different days. Reprinted from Soloviev and Lukas(1997), Copyright 1997, with permission from Elsevier.

Fig. 3. Temperature-depth measurements from SkinDeEP at22.52°N, 109.59°W on 10 Oct. 1999 (graph I). Wind speed(u) and downwelling shortwave radiation (Qsw) (graph II).Temperature differences: SSTskin-SSTsubskin (blue) andSSTsubskin-SSTdepth (red) (graph III). Heat loss differences:Q(SSTskin)-Q(SSTsubskin) (blue) and Q(SSTsubskin)-Q(SSTdepth) (red) (graph IV). Q(SSTskin), Q(SSTsubskin), andQ(SSTdepth) are the surface net heat flux calculated by us-ing SSTskin, SSTsubskin, and SSTdepth as SSTint, respectively.SSTskin was measured with an infrared radiometer. FromWard (2006), Copyright 2006 American Geophysical Un-ion. Reproduced by permission of American GeophysicalUnion.


Fig. 4. NOAA/AVHRR 0.01°-grid SST images at (a) 0645 LST (2145 UT) and (b) 1501 LST (0601 UT) on 27 July 1999. (c) SSTdifference between (a) and (b). (d) Daily mean 0.25°-grid surface wind speed observed with QuikSCAT/SeaWinds on thesame day.

Fig. 5. Seasonal mean day-night difference of the AMSR-E ver. 5 SST produced by Remote Sensing Systems during June 2002–May 2006. Original grid size of the SST is 0.25°, and the seasonal mean is calculated in 1° grids. Nominal observation time isapproximately 0130/1330 LST.


Arabian Sea, the seas around Japan, the north Pacific offNorth America, and the Azores-Bermuda high pressurebelt. Basically, the diurnal warming is large in the tropicsthrough the year. The diurnal SST variation was also stud-ied using geostationary satellite data (Wu et al., 1999;Tanahashi et al., 2003). These authors also reported caseswhen the day-night SST difference reached a few degreesin the Azores-Bermuda high or the seas around Japan.

Gentemann et al. (2003) showed that the TMI SSTdata could detect the diurnal variation, which clearly de-pended on solar radiation and wind speed. The micro-wave sensor has a great advantage in studying SST vari-ations because it can observe both SST and wind speedsynchronously through clouds. On the other hand, theinfrared sensor on the geostationary satellite has anotheradvantage in that it measures SST hourly with a higherspatial resolution, although infrared radiation cannot pen-etrate cloud.

The Advanced Microwave Scanning Radiometer forthe Earth Observing System (AMSR-E) on the Aqua sat-ellite has been operating since June 2002 (e.g., Dong etal., 2006). AMSR-E is the first microwave sensor thatcan observe SST all over the oceans. We calculated sea-sonal mean day-night differences from the AMSR-E ver-sion-5 SST dataset produced by Remote Sensing Systems.The characteristics of the spatial distribution and seasonalvariation of the day-night difference shown in Fig. 5 arebasically consistent with the results of Stuart-Menteth etal. (2003). The spatial and seasonal variations of the day-night difference shown by Stuart-Menteth et al. are notas clear as those in our Fig. 5, especially in the southernhemisphere, mainly due to the lack of the AVHRR SSTsampling hindered by clouds.

In boreal spring before the Indian monsoon, the day-night SST difference is greater than 0.5 K over the north-ern Indian Ocean. A large day-night difference in the highlatitude of the northern hemisphere, and in the subtropi-cal high pressure belt of the southern hemisphere in sum-mer is also clearly captured. Around 45°S in the IndianOcean and the Pacific Ocean sections the mean day-nightdifference is less than 0.2 K throughout the year due tothe strong westerlies. Interestingly, in the high-latituderegion around 60°S the mean day-night difference reaches0.3–0.5 K in austral summer. The diurnal SST variabilityaround the Antarctic has rarely been reported. This needsto be investigated in future study.

In the narrow zonal area in the eastern equatorialPacific west of the Galapagos Islands, the day-night dif-ference becomes notably large, reaching a maximum inboreal spring and a minimum in boreal autumn. Deserand Smith (1998) and Clayson and Weitlich (2005, 2007)also indicated that the diurnal SST amplitude has a localmaximum over the cold tongue in the eastern equatorialPacific. The diurnal amplitude in this area becomes larger

from boreal winter to spring. This is consistent with theanalysis of buoy data by Cronin and Kessler (2002). Ac-cording to Clayson and Weitlich (2005, 2007), this pat-tern disappeared in the mature phase of the 1997–98ENSO event. An ENSO event changes the spatial and tem-poral variations of the diurnal SST amplitude as a resultof the characteristically different surface conditions as-sociated with ENSO in this region (Cronin and Kessler,2002; Kawai and Kawamura, 2005). Using satellite data,Kawai and Kawamura (2005) and Clayson and Weitlich(2007) also indicated that the diurnal SST amplitude inthe western equatorial Pacific varies in association withMJO.

4. Modeling Diurnal Variations near the SurfaceMany kinds of numerical or empirical models have

been used to investigate the diurnal variations of the up-per ocean. However, no model can simulate the diurnalvariations perfectly (Soloviev and Lukas, 2006). In gen-eral, numerical models concerned with simulations of thediurnal variations are roughly categorized as diffusion-type, bulk- or slab-type, and transilient models. Solovievand Lukas (2006) also provided general information aboutthe modeling of the diurnal variations. In addition, theyshowed a simulated diurnal variation in the Pacific warmpool by a transilient model. This section reviews numeri-cal models for the simulation of the diurnal variations,except the transilient model described by Soloviev andLukas (2006).

4.1 Diffusion modelsDiffusion models are subdivided into the following

categories: (1) which parameterize the turbulent mixingand eddy-diffusion directly in empirical or semi-empiri-cal ways; (2) which estimate turbulence quantities by tur-bulent closure at each level. The former, based on ourknowledge of the Monin-Obukhov similarity theory inthe surface boundary layer, are the models proposed byKondo et al. (1979) and Large et al. (1994). The latterare those of Mellor and Yamada (MY) (1982), and modi-fied version of MY (e.g., Kantha and Clayson, 1994).

Kondo et al. (1979) proposed a simple one-dimen-sional model to reproduce observed behavior of the sur-face current and daily sea temperature within 10-m depthnear the sea surface. Their model specializes in simulat-ing the surface boundary layer. Results of the numericalexperiment suggested that the diurnal range of upper-layertemperature was certainly dependent on wind speed. Thediurnal amplitude of simulated SST reached its peak ofnearly 2 K when the 10 m-height wind speed was 2.5ms–1 on a clear equinox day at 35°N. They also indicatedthat the more stable the sea surface layer was, the fasterthe surface drift current, due to inhibition of downwardmomentum transfer.


Kawai and Kawamura (2000) modified Kondo et al.’smodel by replacing dimensionless shear functions to maketurbulent transfer larger for stable cases. Kawai andKawamura (2000) were able successfully to simulate avery sharp diurnal thermocline within 1-m depth observedin Mutsu Bay (Yokoyama et al., 1995) by using both themodified version of Kondo et al.’s model and the sec-ond-order turbulence-closure model developed by MY(Fig. 6).

4.2 Bulk or slab modelsModeling under the assumption of a constant profile

of sea temperature, salinity and current within a mixedlayer is in general categorized as a bulk or slab model(hereafter, bulk model). The bulk model is subdivided intointegral and layer types. Integral models represent turbu-lent mixing at the base of the mixed layer by entrainment.Some of the entrainment rate parameterizations are de-rived from the kinetic energy equation under the condi-tion that the energy equation is conserved. In general, avelocity jump has to be assumed at the bottom of themixed layer in the integral models. Layer models use amodeling methodology that estimates turbulent kineticenergy in every vertical layer. Simplified versions of thelatter models have been developed recently. We here di-vide bulk models into multilayer type and simplified sin-gle layer type. We do not refer to the integral type in thepresent review.a. Multilayer model

A bulk model proposed by Price et al. (1986) hasbeen frequently applied to studies of the diurnal SST vari-ation. The model is often called the “Price-Weller-Pinkel(PWP)” model. Its numerical scheme is based on a dy-namic instability model (DIM) (Price et al., 1978). Theconcept of DIM is that the rate of change of potentialenergy during deepening of the mixed layer balances thatrate of energy released from the mean flow by the reduc-tion of vertical shear. The PWP model is a modified ver-sion of the DIM by Price et al. (1978), including a mix-ing process in the stratified part below the mixed layer.

It is worth noting, though, that the diurnal SST am-plitude simulated by the PWP model tends to be too largewhen compared with observations (Kantha and Clayson,1994; Large et al., 1994). Large et al. (1994) indicatedthat this disagreement of the PWP model could be causedby insufficient vertical mixing. SST is more sensitive tothe strength of the vertical thermal diffusion when thesurface stratified layer becomes less than 1-m thick un-der calm and clear conditions. The representation of thevertical mixing in the stable stratified layer is one of thecrucial keys to predict diurnal SST variation accurately,but is still imperfect. The mixed layer models mentionedhere do not take the turbulence generated by wave break-ing and Langmuir circulation into consideration. These

effects strengthen the vertical mixing. Recently, effortshave been made to incorporate these effects into the mixedlayer model (e.g., Noh et al., 2004), which will improvethe reproduction of the near-surface temperature varia-tion.b. Simplified model

If we desire to simulate sharp diurnal thermoclineand diurnal SST variations in numerical models, we needa fine vertical grid interval near the surface (Bernie etal., 2005). This requires an enormous computational load.In order to avoid it, some simplified models have beenproposed that specialize in simulating the diurnal varia-tion near the surface. Fairall et al. (1996) proposed agreatly simplified form of the PWP model that ignoresfull mixed-layer dynamics in order simply to predict thediurnal variation of the near-surface temperature only.They assumed that the temporal integrals of surface heatand momentum fluxes are confined within the warm layer,and the temperature profile in the warm layer is linear(Fig. 7(a)). The depth of the warm layer is determined byrequiring that the bulk Richardson number is no greaterthan a critical number. Their warm layer model is well-known and is often utilized for air-sea flux estimation incombination with their cool-skin model.

The Fairall et al. model is simple and convenient,but the linear temperature profile does not always agreewith observations (e.g., Ward et al., 2004a). Zeng andBeljaars (2005) developed another simple scheme to es-timate SSTskin by assuming a more realistic profile shape(Fig. 7(b)). The temperature profile in the warm layer T(z)is given by the following formula:

T zz

DT D

TT( ) = − −

−

− ( )[ ] ( )SST SSTsubskin subskinδδ

ν

, 1

where z is the depth, δ is the depth of the skin layer, andDT is the depth of the warm layer. An empirical param-eter ν is assumed to be 1 in the Fairall et al. model and0.3 in the Zeng-Beljaars model. Zeng and Beljaars (2005)mentioned that the diurnal variation of ocean tempera-ture usually becomes small enough at 2~4-m depth, whichcorresponds to SSTfnd mentioned in Section 2. They de-termined DT in advance empirically within this depthrange. The eddy diffusion coefficient in the surface layerwas determined on the basis of the Monin-Obukhov simi-larity theory.

For the purpose of reproducing the diurnal cycle ofSST in ocean general circulation models (OGCM),Schiller and Godfrey (2005) proposed a simple methodthat incorporates an extra variable-depth diurnal sublayerin the top model layer (Fig. 7(c)). The sublayer existsonly when the total buoyancy received in the top layer ispositive. Their sublayer model is based on the concept of


DIM, like that of Fairall et al. (1996). Schiller andGodfrey’s model could well reproduce the observed di-urnal cycle of 2.5-m-depth temperature. However, notethat their model does not calculate SSTskin, and the tem-perature in the sublayer is assumed to be independent ofdepth. Hence the SST simulated by their model is expectedto be a little different from SSTskin. Furthermore, we needto bear in mind that the simplification of the models in-troduced in this subsection would neglect some dynami-cal processes in the upper ocean, which may affect air-sea interaction.

4.3 Empirical parametric modelsThe diurnal SST variation depends primarily on wind

speed and solar radiation, so the diurnal SST amplitudecan be estimated from these meteorological data. Price etal. (1987) proposed an empirical model to evaluate thediurnal amplitude of 0.6-m-depth temperature. They re-lated the amplitude of SST0.6m with surface stress andsurface heat flux. Another simple model proposed byWebster et al. (1996) included precipitation rate as wellas wind speed and solar radiation based on mixed-layermodel simulations during COARE. Their empirical modelof the diurnal amplitude of SSTskin (∆SSTskin) has the fol-lowing form:

∆SSTskin

= + ( ) + ( ) + ( )[ ] + ( ) ( ) + ( ) ( )f a PS b P c U d PS U e Uln ln , 2

where PS is the daily peak surface solar radiation(W m–2), P is the daily mean precipitation rate (mm h–1),and U is the daily mean wind speed (m s–1). a, b, c, d, e,and f are the coefficients (Table 2). The estimated ∆SSTskinis shown in Fig. 8. If there is precipitation, ∆SSTskin be-comes higher due to the saline stratification. The ∆SSTskinestimated by Webster et al.’s empirical model cannot ex-ceed 3 K, even in the extremely calm and strong insola-tion case. This upper limit seems too small in compari-son with the observational studies mentioned previously.They produced the model (2) based on the simulation re-sults of Kantha and Clayson’s (1994) mixed layer modelunder various forcing conditions. The reason for thesmaller upper limit of model (2) may be that the sensitiv-ity of the mixed layer model to the forcing was imper-fect.

The effects of precipitation and latent heat flux willcertainly be needed for better estimation of the diurnalamplitude of SST (e.g., Price et al., 1987; Soloviev andLukas, 1997; Kawai and Kawamura, 2003). However, theyhave a secondary effect on the diurnal SST variation, andthe diurnal amplitude can even be approximately evalu-ated from wind speed and solar radiation only (Kawaiand Kawamura, 2002; Gentemann et al., 2003; Claysonand Weitlich, 2005). In reality it is not easy to know dailyprecipitation rate accurately over a wide ocean region.Stuart-Menteth et al. (2003) estimated the diurnal ampli-tude of SST over the globe using Kawai and Kawamura’s(2002) empirical formula, which uses only wind speedand solar radiation, and confirmed that the spatial distri-bution of the estimated diurnal amplitude agreed well withthat of the day-night satellite SST difference.

While the above models can estimate only the am-plitude, which is defined as the daily maximum-minimumdifference, Zeng et al. (1999) and Gentemann et al. (2003)proposed simple empirical models that can estimate thediurnal SST rise from the morning minimum at each hour.Clayson and Curry (1996) also developed a method toestimate the diurnal SSTskin cycle. They assumed a co-sine-shaped diurnal cycle with the amplitude estimatedby Webster et al.’s empirical model (2), and added it todaily predawn SSTskin, which was determined from satel-lite-derived SSTskin data by linear interpolation. Further-more, Li et al. (2001) proposed a simple technique to es-timate SSTskin at each hour in a numerical model by ap-plying Webster et al.’s model. Li et al. (2001) assumedthat the variation of SSTskin was determined by the sur-face wind and solar radiation one hour previously, andthe hourly anomaly of SSTskin from its daily mean at thei-th hour on the j-th day (∆Ti,j) could be expressed in thefollowing form:

∆ Γ ΓTi

i j i j i ji

, , , ,= −

− − +

( )− −=

∑1 11

241

121

12 1

123′

′

Fig. 6. Vertical temperature profiles in Mutsu Bay at 1430 LSTon 7 July 1992. Solid line and open circles represent ob-served values. Broken line and asterisks represent tempera-ture simulated by the second-order turbulence-closure modelof Mellor and Yamada (1982). Chain line and pluses repre-sent those simulated by Kawai and Kawamura’s (2000)model. Reproduced from Kawai and Kawamura (2000).


Γ

Γ

i j i j i j

i j i j i j

i j

i j i j

f a S c U

d S U e US

S

, , ,

, , ,

.

, .

ln

ln ,, ,

= + ( ) + ( ) + ( ) ( ) + ( )

>

= ≤

( )0

0 0

4

where Si,j and Ui,j is the hourly surface solar radiationand wind speed at the i-th hour on the j-th day, respec-tively. The precipitation is ignored here. The time of lo-

cal sunset is defined as i = 1, and Γi ji

′′

, −=

∑ 11

24

is the sum of

Γ on the previous day. They showed that theirparameterization could well reproduce diurnal SSTskinvariations. Since these simple schemes introduced hereuse daily mean meteorological values and/or previous-day information, it may be difficult to utilize theseschemes for discussing simultaneous air-sea interactionprocesses in a coupled model. However, they will be use-ful to test the sensitivity of the atmosphere to the diurnalvariation of SST.

5. Effect of Diurnal Thermocline on Air-Sea FluxEstimations

5.1 Air-sea heat flux estimationSverdrup et al. (1942) suggested the importance of

the diurnal SST variability on air-sea heat exchange. Sincethe atmosphere contacts the sea skin, not the water at afew meters depth, evaluating the temperature differenceacross the warm layer and skin layer is indispensable foraccurate air-sea heat flux estimation. An error of 1 K inSSTskin can lead to an error of 27 W m–2 in net surfaceheat flux in the tropical western Pacific (Webster et al.,1996). Furthermore, Cornillon and Stramma (1985)

showed an example in the north Atlantic where monthlymean SST was higher by about 0.2 K in the case that di-urnal SST variations were included than in the case thatthey were ignored. This difference reduces the net heatflux of 5 W m–2 entering the ocean.

Fairall et al. (1996) showed that the cool skin de-creased the net heat flux from the ocean by about 11W m–2 and the warm layer increased it by about 4 W m–2

on average over 70 days during COARE. The effect ofthe warm layer may seem to be fairly small, but this wasthe mean value including the cases when the warm layerdid not develop. Fairall et al. (1996) and Ward (2006)indicated that the net heat flux from the ocean can in-crease 50–60 W m–2 in the daytime under calm and clearconditions due to the effect of the warm layer (Fig. 3).Clayson and Curry (1996) estimated surface turbulent heatfluxes during COARE from satellite data and comparedthem with in situ measurements. They showed that deter-mining the fluxes every 3 h from interpolated satellite-derived input variables, i.e., including diurnal cycles inSSTskin and atmospheric variables, improved the estimate

Fig. 7. Schematics of vertical temperature profile near the surface assumed in (a) Fairall et al.’s (1996) model, (b) Zeng andBeljaar’s (2005) model, and (c) Schiller and Godfrey’s (2005) sublayer scheme. DT is the depth of the warm layer (sublayer).Zk=1 in (c) is the thickness of the top layer of an ocean mixed model. δ is the depth of the skin layer. Ttop and Tbot(z) in (c) arethe temperatures in the sublayer, and the layer under the sublayer, respectively. Tbot(z) may depend on depth, but is not solvedin the scheme. In (a) and (c) DT is time-dependent, while it is given in advance empirically in (b).

Coefficient U > 2 m s–1 U ≤ 2 m s–1

f 0.262 0.328a 0.00265 0.002b 0.028 0.041c –0.838 0.212d –0.00105 –0.000185e 0.158 –0.329

Table 2. Coefficients for the empirical formula (2). Reproducedfrom Webster et al. (1996).


of daily-mean surface fluxes. However, they did not evalu-ate the effect of the diurnal variation of SSTskin on thefluxes.

Zeng and Dickinson (1998) investigated the impactof the diurnal variation of SSTskin on surface fluxes overthe equatorial Pacific using TOGA Tropical AtmosphereOcean (TAO) buoy hourly data from 95°W to 137°E in1990–1996. The surface latent and sensible heat fluxesshowed clear diurnal variability, and the average diurnalamplitudes of the latent and sensible heat fluxes were 19.7and 5.6 W m–2, respectively. They also calculated the heatfluxes by replacing hourly SSTskin with daily or monthlymean SSTskin. Figure 9 shows the examples of the differ-ences between the heat fluxes with the hourly SSTskin andthose with the daily or monthly SSTskin. Evidently thediurnal cycle in SSTskin is the main cause of the diurnalvariability of latent and sensible heat fluxes. They sug-gested that numerical modeling may require the inclu-sion of the diurnal SSTskin variation. Parsons et al. (2000)also showed that the average diurnal amplitudes of sur-face sensible and latent heat fluxes were about 4 and 35W m–2, respectively, within the inner intensive flux arrayof the COARE experiment in mid-November 1992.

Schiller and Godfrey (2005) examined the effect ofthe diurnal variability of SST on surface latent heat fluxduring COARE using a one-dimensional coupled modelwith their sublayer scheme (see Subsection 4.2). Use of

this scheme increased the latent heat flux during the day-time by 10–20 W m–2 and reduced it in the nighttime by0–5 W m–2. The increase in time-mean net heat loss ofthe ocean was about 10 W m–2. Zeng and Beljaars (2005)reported that incorporating their SSTskin scheme (see Sub-section 4.2) into an operational forecasting model changedensemble annual mean surface latent heat flux by morethan 10 W m–2 over several regions in the north Atlantic.

The authors also checked the impact of the warmlayer on the air-sea heat transfer by a simple numericalexperiment. The test data used here were obtained with amoored buoy of the Triangle Trans-Ocean buoy Network(TRITON) in the western tropical Pacific at 2.07°N,138.06°E during 3–13 March 2004. The authors simu-lated near-surface temperature using the buoy-observedmeteorological data and Kawai and Kawamura’s (2000)one-dimensional model. The details of the observationsand the model simulation are reported in Kawai et al.(2006b). The diurnal temperature variation was large on3, 7 and 9 March, and the model could reproduce the vari-ation of SST0.3m approximately (Kawai et al., 2006b). Thissimulation result of SSTskin is shown in Fig. 10(a) with asolid line, and is called the “control run”. The layer be-tween the sea surface and 1.5-m depth was then forciblymixed by setting the minimum of the eddy diffusion co-efficients to 5.0 × 10–4 m2s–1 above 1.5-m depth. Thissimulation is referred to as the “no-warm-layer run” (bro-

Fig. 8. Diurnal amplitude of SSTskin estimated by Webster et al.’s (1996) empirical model as a function of daily peak solarradiation for different values of daily mean wind speed and precipitation. Solid, broken, and dotted lines represent 0, 1, and 5mm h–1 of daily mean precipitation rate, respectively. Black, magenta, red, blue, and green lines represent 0.1, 1, 3, 5, and 10m s–1 of daily mean wind speed, respectively.


ken line in Fig. 10). In the no-warm-layer run the diurnalthermocline was destroyed and the temperature becamevertically homogeneous within 0–1.5 m depth, even inthe daytime (Fig. 10(b)). The diurnal amplitude of SSTskindecreased by about 1.5 K in the no-warm-layer run in thedaytime of 7 and 9 March. The no-warm-layer run al-most corresponds to the case that a model applies a coarsevertical grid of 1.5 m, which cannot resolve the shallowwarm layer.

If the warm layer cannot be reproduced correctly,the surface net heat flux from the ocean decreases by 20–40 W m–2 in the daytime (Fig. 11). The integrated differ-ence of the net heat flux through a day exceeds 0.9MJ m–2 on 7 and 9 March (Table 3). About 64% of thetotal heat difference is due to latent heat. The effect ofthe warm layer is to retain the incident solar energy nearthe sea surface and increase the heat transfer back to theatmosphere, mainly as latent heat. The heat of 0.9MJ m–2, which can raise the temperature of the 10-m-thick water column by only 0.02 K, may not be importantfor the ocean, but it will not be negligible for the atmos-phere because the thermal capacity of the air is muchsmaller and such an amount of excessive heat from theocean can destabilize the lower atmosphere.

Recently several kinds of global surface flux datasetshave been developed using satellite and/or reanalysis data(cf. Kubota et al., 2003; Curry et al., 2004). In some ofthese datasets, the SST produced by optimum interpola-tion (e.g., Reynolds and Smith, 1994; Reynolds et al.,2002) is used for the flux calculation. However, such SSTdata lack diurnal and day-to-day variability. Yu et al.(2004) suggested that the absence of the high-frequencyvariations in SST appeared to cause the degradation inthe accuracy of air-sea temperature and specific humid-ity differences. Consideration of the high-frequencySSTskin variations will be necessary to improve the qual-ity of surface flux data.

5.2 Air-sea gas flux estimationThe solubility of gases in seawater depends on tem-

perature. Hence diurnal increases in near-surface tempera-ture can change the concentrations of CO2 and O2 andmodify the air-sea gas flux. Researchers working on theair-sea gas exchange have been paying attention to thediurnal warming and the skin effect. For example,Soloviev et al. (2001) reported an observed example thatdissolved oxygen concentration just near the surface (shal-lower than 0.1-m depth) was lower by about 5 ml l–1 thanthat at 0.5-m depth or deeper in association with the for-mation of the diurnal thermocline. McNeil and Merlivat(1996) revealed the diurnal variations of water tempera-ture and dissolved CO2 fugacity (fCO2) observed at 2-mdepth in the Mediterranean Sea, and indicated that thefCO2 predicted from observed SST2m and an fCO2-tem-

perature dependence of 4.23% K–1 for constant total CO2was similar to the observed fCO2 (Fig. 12). This meansthat fCO2 near the surface can vary widely in associationwith diurnal warming. The diurnal amplitude of the cal-culated fCO2 was 10–20 µatm.

Ward et al. (2004a) evaluated the effects of the skinlayer and the warm layer on the air-sea CO2 exchange inthe eastern equatorial Pacific during the GasEx-2001cruise. Basically, the skin effect consistently suppressesthe CO2 emission from the oceans through a day, whilethe formation of the warm layer increases it only in thedaytime. According to their evaluation, the mean decreaseof the surface CO2 flux due to the skin effect was about2% with a maximum of almost 4%. The increase of theCO2 flux due to the warm layer could exceed 6% tempo-rarily, although the mean value throughout the observa-tion period was only about 0.7%. They implied that theeffect of the warm layer may be less important for theair-sea CO2 exchange than the skin effect, because whilethe warm layer forms only in the daytime of a calm andclear day, the skin layer exists even in windy conditions(Donlon et al., 2002). The relative increase due to the

Fig. 9. Mean diurnal cycles of surface flux differences at 0°N,156°E (a–b), and 2°S, 95°W (c–d). Latent (a and c) andsensible (b and d) heat flux differences using hourly versusdaily (monthly) mean SSTskin are denoted by solid (dotted)lines. Abscissa represents local time. From Zeng andDickinson (1998), Copyright 1998 American GeophysicalUnion. Reproduced by permission of American Geophysi-cal Union.


warm layer effect shown by Ward et al. (2004a) was cer-tainly small, but this can correspond to a large absoluteincrease in the regions such as the eastern tropical Pa-cific where the absolute value of the CO2 flux is large.They also indicated that the estimated difference of fCO2across the warm layer of a few meters thickness can reach20 µatm or more (Fig. 13). In the eastern equatorial Pa-cific, the diurnal SST amplitude becomes larger duringLa Niñas and lower during El Niños. Hence it is expectedthat the impact of the warm layer on the surface CO2 fluxwill vary with the ENSO cycle (Cronin and Kessler, 2002).

The skin effect on the global CO2 budget has alsobeen assessed by several researchers (e.g., Sarmiento andSundquist, 1992; Robertson and Watson, 1992; Van Scoyet al., 1995; Wong et al., 1995), but this issue is beyondthe scope of this paper, and we do not review it here. Thestudies mentioned in this subsection indicated that a care-ful consideration of the ocean surface boundary layer andits high-frequency variability will be significant in stud-ies of the global material circulation and climate change.

6. Impact on the AtmosphereThe diurnal variation of SST is strongly affected by

meteorological conditions. Can the diurnal SST variationreally significantly affect the properties of the atmos-phere? As yet, we do not know the impact of the diurnalSST variation on physical properties or processes in theatmosphere, especially in the boundary layer. Large diur-nal SST variations must be accompanied by a weak wind,which suppresses the turbulent heat transfer from theocean to the atmosphere. Zhang (2005) pointed out that“the atmosphere does not see SST; it only senses it throughsurface fluxes.” From this viewpoint, paradoxically, theatmosphere near the surface may sense that the sea sur-face is cool in calm and clear conditions. Chen and Houze(1997) indicated that the diurnal cycle in the surface airtemperature was not completely dependent on that inSSTskin, although they suggested the importance of thediurnal heating of the sea surface on cloud convectionover the Pacific warm pool.

On the other hand, as mentioned in Subsection 5.1 ithas been reported that the diurnal SST rise in the equato-rial Pacific can increase the surface net heat flux by theorder of 10 Wm–2, which is probably non-negligible foratmospheric physical processes. Several researchers as-sume that the diurnal SST variability may have someimpact on the atmosphere. For example, Dai and Trenberth(2004), using a fully coupled climate system model with-out the diurnal SST variation, indicated that simulateddiurnal cycles in surface air temperature, pressure andprecipitation over the oceans were much weaker than theobserved values. They inferred that the lack of the diur-nal cycle in SST was a significant deficiency. The diur-nal variability of SST in the tropics is basically large,

Fig. 10. (a) Time series of the model-simulated SSTskin in theno-warm-layer run (broken line), and that in the control run(solid line) at 2.07°N, 138.06°E in March 2004. (b) Theirvertical temperature profiles at 1600 LST on 9 March.

Fig. 11. Difference of net air-sea heat flux between the tworuns (control run minus no-warm-layer run, upward is posi-tive) at 2.07°N, 138.06°E in March 2004. Shortwave radia-tion is not included.


3 March 7 March 9 March

Net 0.649 0.912 0.990Sensible heat 0.080 0.112 0.117Latent heat 0.417 0.590 0.631Longwave radition 0.152 0.210 0.242

Table 3. Daily-integrated differences of the surface heat fluxesbetween the control run and the no-warm-layer run. Unit isMJ m–2.

Fig. 12. Observations during 5 days in August 1995 of 2-m-depth water temperature (T, dashed line) and fugacity ofCO2 (fCO2, bold solid line) at a mooring site between Niceand Corsica in the Mediterranean Sea (43.42°N, 7.87°E).Thin solid line is the predicted fCO2 from the observed Tand an fCO2-temperature relation of 4.23% K–1 for constanttotal CO2. From McNeil and Merlivat (1996), Copyright1996 American Geophysical Union. Reproduced by permis-sion of American Geophysical Union.

and has been intensively investigated since COARE. Inthis section we first review studies and hypotheses on theeffect of the diurnal SST variation on the tropical atmos-phere. Other topics in the mid and high latitudes are thensummarized.

6.1 TropicsThe diurnal variability of cloud convection over the

ocean has been observed, although its mechanism has notyet been completely solved. In general, the diurnal varia-tions of cumulus convections over the ocean and land aredifferent from each other. The convective activity is en-hanced in the late afternoon to evening over continentsand large islands, while it attains its maximum in the earlymorning over the ocean (e.g., Gray and Jacobson, 1977;Janowiak et al., 1994; Yang and Slingo, 2001; Dai andTrenberth, 2004). Various kinds of mechanisms have beenproposed for the formation of diurnal deep convectionover the ocean: the direct interaction between radiationand convection (Randall et al., 1991); the effect of thehorizontal distribution of clouds on radiation (Gray andJacobson, 1977); the radiative interaction between sur-face and clouds (Chen and Houze, 1997); the diurnal vari-ation of available precipitable water due to the diurnalradiative cooling/heating cycle (Sui et al., 1997a); andgravity wave forcing induced by the nearby continentaldiurnal cycle of convection (Mapes et al., 2003).

Analyses of the COARE observation results revealeda more detailed aspect of the diurnal variation of convec-tion over the warm pool. During the convectively activephase of MJO, the large, deep convective systems tendedto reach a maximum before dawn, as mentioned above.On the other hand, during the convectively suppressedphase of MJO, when the diurnal SST variation was large,shallow precipitating clouds were most abundant (Fig.14). Many of these shallow clouds occurred in the after-noon near the time of maximum SST, unlike the diurnalvariation of the deep convection in the active phase (e.g.,Chen and Houze, 1997; Sui et al., 1997a; Johnson et al.,1999). Parsons et al. (2000) showed from COARE sound-ing data that there was a detectable diurnal cycle in con-vective inhibition (CIN), with a minimum in the late af-ternoon just preceding the maximum in convective activ-

ity. Parsons et al. (2000) and Chen and Houze (1997)claimed that the absorption of shortwave radiation in theatmospheric boundary layer will be as important (or moreimportant) in the diurnal variation in CIN as (than) thediurnal cycle in SST and the resulting changes in thefluxes. Slingo et al. (2003) suggested the possibility thatthe diurnal SST rise may act as a trigger for the shallowcloud convection. The basic paradigm proposed by themis as follows: the diurnal cycle in SST leads to a trigger-ing of convection in the inactive phase of MJO. In turnthe cumulus congestus clouds gradually moisten the freetroposphere and prepare a favorable condition for deepconvection. This preconditioning may set the time scalefor the following active phase of MJO. These hypotheseshave not yet been corroborated.

Li et al. (2001) performed numerical experimentsusing a global atmospheric model with or without the di-urnal variation of SSTskin. They indicated that the phasesof the intraseasonal variations of surface flux and pre-cipitation simulated with diurnal SSTskin variations werecloser to those of the observations in the warm pool dur-ing COARE, compared to those simulated without thediurnal SSTskin variations. The diurnal SSTskin variationbrought the increase of precipitation especially over thetropical Indian Ocean and the western tropical Pacific,although the ratio of the increase to the mean value wasnot more than 10%.

Woolnough et al. (2007) also examined the impact


of the diurnal mixing of the upper ocean on MJO by cou-pled model experiments. They compared the result ofconstant-SST simulation with the result simulated by cou-pling to a full dynamical ocean model of 10-m verticalresolution in the upper ocean, or that by coupling to aone-dimensional ocean mixed layer model of 1-m reso-lution. This 1-m resolution mixed layer model could re-produce large diurnal and intraseasonal SST variations.The experiment with the mixed layer model showed thebest improvement in prediction skill, especially for thephase of the MJO over the Indian Ocean and the westernPacific. They indicated the role of the ocean in determin-ing the propagation characteristics of the MJO, and thesignificance of the representation of the diurnal cycle inthe upper ocean.

Fig. 13. Series of SkinDeEP temperature profiles acquired on8 Feb. 2001 in the eastern equatorial Pacific (GasEx-2001)and the extrapolation of the aqueous fCO2 to the surfacefrom an fCO2-temperature dependence of 4.23% K–1 forconstant total CO2. The local times are indicated for eachplot. From Ward et al. (2004a), Copyright 2004 AmericanGeophysical Union. Reproduced by permission of Ameri-can Geophysical Union.

Clayson and Chen (2002) investigated the sensitiv-ity of the atmosphere to SST as the lower boundary con-dition in the tropical Pacific using a coupled single-col-umn model. They showed that use of the simulated SSTskinas the interfacial temperature rather than SSTdepth resultedin large differences in the atmospheric profiles of tem-perature, moisture, and cloud amount. Figure 15 showsthe cloud amount simulated with the SSTskin (baselinesimulation), and that with the SST4.5m (4.5-m tempera-ture simulation). The SST4.5m was higher by 0.25 K thanthe SSTskin on average due to the skin effect, and showedless diurnal variability. The baseline simulation has lowerlow-level cloud amounts during periods 1 and 3, andhigher amounts during period 2, compared with the 4.5-m temperature simulation. The cloud amount differencesin the low level are larger than that in the mid level. Oneof their interesting indications is that both the skin effectand the diurnal variability are important for the atmos-phere, and which of the effects is dominant varies withthe periods. Clayson and Chen (2002) also indicated thatthe model atmosphere was sensitive to the scheme of sur-face turbulent heat fluxes.

Deser and Smith (1998) indicated from TAO buoydata that the mean diurnal amplitude of SST showed alocal maximum over the cold tongue in the eastern equa-torial Pacific. They proposed a hypothesis that this largediurnal SST variation over the cold tongue may affectthe zonally symmetric diurnal cycle of equatorial winddivergence.

6.2 Mid and high latitudesFlament et al. (1994) found streaks of large diurnal

sea surface warming that occurred in spring off Califor-nia from satellite data. These streaks were at least 50 kmlong and 4–8 km wide. They hypothesized that thesestreaks may interact with roll-like circulations in the at-mospheric boundary layer, and proposed two kinds ofhypotheses to explain this phenomenon. These hypoth-eses are interesting, but nobody has verified them yet.

Kawai et al. (2006a) investigated the impact of diur-nal sea surface warming on a local atmospheric circula-tion over Mutsu Bay, which is located at the northern endof Honshu Island in Japan around 41°N, 141°E, on a clearsummer day. Over this region small sea breeze circula-tions and mountain up-slope wind circulations are com-bined during the daytime, and a unique atmospheric cir-culation is formed. The result of their simple model ex-periment showed that the SSTskin rise in the daytime weak-ens this atmospheric circulation due to the decrease ofthe land-sea temperature difference. This results in theincrease in surface air temperature over coastal areas. Theeffect of the diurnal sea surface warming on the sea breezecirculation is expected to obtain over other coastal areasthroughout the world, especially in the tropics. Yang and


became large in the Bay of Bengal and the South ChinaSea during the transition period of the Asian monsoon inboreal spring. It was also reported from in situ observa-tions that the diurnal SST cycle in the South China Seawas dominant before the onset of the monsoon, and de-creased thereafter (D. Wang, the presentation in the 11thOcean Observations Panel for Climate, 2006). A suggestedpossibility was that the diurnal variability of SST mayaffect the monsoon onset, but no corroboration has yetbeen obtained.

Kawai and Kawamura (2005) indicated that the di-urnal amplitude of SST also became large, even in theSea of Okhotsk from spring to summer. Low-level cloudsand fog frequently cover this region in summer. Tachibanaet al. (2004) pointed out that the appearance and disap-pearance of fog in the Sea of Okhotsk will be controlledby air-sea interaction. They reported from ship observa-tions that when warm air was advected in the lowest level,the air cooled while the upper ocean warmed. In this casethe atmospheric mixed layer could not develop and fogdid not occur, which led to strong insolation at the seasurface. Therefore, thermal stratification was formedwithin a few meters depth. The large diurnal rise of SSTmay, in turn, change the stability of the lowest atmos-phere. Furthermore, the formation of the shallow diurnalstratification may affect the variations of SST and theocean mixed layer on a longer time scale (see Subsection7.1).

7. Issues in Modeling and Observation of DiurnalSST Variation

7.1 Numerical modelinga. Surface forcing

In order to reproduce realistic diurnal variation ofSST using an ocean model, accurate surface forcing isrequired as a boundary condition. In particular, insola-tion with a diurnal cycle is important in reproducing thediurnal variation. Recently many model researchers haveinvestigated the effect of diurnal variability of surfaceforcing on modeling of SST and ocean mixed layer (e.g.,Sui et al., 1997b; Shinoda and Hendon, 1998; McCrearyet al., 2001; Schiller and Godfrey, 2003; Bernie et al.,2005; Lee and Liu, 2005; Shinoda, 2005; Danabasoglu etal., 2006). These studies indicate that the diurnal varia-tion of surface forcing, especially that of insolation, playsan important role in reproducing diurnal and intraseasonalvariations, or a mean state in the upper ocean. The diur-nal change of the mixing process of the upper layer is notonly related to the diurnal SST variability, but is also es-sential for the intraseasonal SST variation. The inclusionof the diurnal cycle of insolation enables one to simulatea more realistic temperature and depth of mixed layer.The temporal mean of tropical SST simulated with the

Fig. 14. Daily-average number of low or cumulus (0–4 km),middle or congestus (5–9 km), and high or cumulonimbus(11–16 km) radio-echo tops for a cruise of R/V Vickers dur-ing COARE, and SST observed with the Improved Mete-orological instrument (IMET) buoy at 1.75°S, 156°E. In theupper three panels, solid curve segments refer to periodswhen convective echoes organized on the Mesoscale Con-vective System (MCS) scale (>100 km) and dotted segmentsto periods when only sub-MCS or isolated cells existed.Reproduced from Johnson et al. (1999).

Slingo (2001) indicated that the strong diurnal signals ofconvection over land were spread out many hundreds ofkilometers away over the Bay of Bengal and the coastalseas in the Maritime Continent. They suggested that thisphenomenon is affected by complex land-sea and moun-tain-valley breezes. The diurnal cycle in SST may affectthis phenomenon through modification of the land-seabreeze circulation. Yang and Slingo (2001) and Slingo etal. (2003) point to the need for a proper parameterizationof the effect of land-sea breezes in a numerical model forbetter simulation of the diurnal cycle in convection. Theeffect of the diurnal SST variation should also be includedin the parameterization or model.

Stuart-Menteth et al . (2003) and Kawai andKawamura (2005) showed that the diurnal SST variation


diurnal cycle of insolation tends to be higher than with-out it.

Figure 16 shows the result of a numerical experi-ment performed by Bernie et al. (2005), who simulatedmixed layer depth and temperature with hourly surfacefluxes and with daily mean fluxes, respectively. The am-plitude of the intraseasonal SST variation clearly de-creases if the diurnal variations of the surface fluxes areneglected. The mixed-layer depth simulated with thehourly fluxes becomes a little deeper than that with thedaily fluxes. Sui et al. (1997b) insisted that, because ofthe asymmetric heating rate of the diurnal cycle, the vari-ation of mixed-layer properties on the diurnal timescaleis nonlinearly related to the intraseasonal variability. Thediurnal change of the ocean mixed layer will affect thephase of intraseasonal atmospheric variation through theamplification of the intraseasonal SST variation (cf. Li etal., 2001; Woolnough et al., 2007). The inclusion of themixed-layer deepening/shoaling process on the diurnalscale cannot be neglected in biological modeling(McCreary et al., 2001).b. Solar extinction modeling

Unlike longwave radiation, sensible and latent heatfluxes, shortwave radiation can penetrate the ocean. De-termination of vertical distribution of warming byshortwave radiation in the upper ocean is critical to re-producing accurate diurnal and intraseasonal variationsof SST (e.g., Kantha and Clayson, 1994; Sui et al., 1997b;Shinoda, 2005; Wick et al., 2005; Ward, 2006; Claysonand Weitlich, 2007). Sui et al. (1997b) pointed out thatrealistic diurnal and intraseasonal SST variations in the

Fig. 15. Time series of (a) daily-averaged mid-level (400–700 hPa) cloud amount, and (b) low-level (below 700 hPa) cloudamount for the baseline simulation (solid line) and the 4.5-m temperature simulation (dashed line) with a coupled atmos-phere-ocean single-column model during COARE. Reproduced from Clayson and Chen (2002).

tropics cannot be reproduced if an inappropriateparameterization for shortwave radiation is used.

An approximate formula of a polynomial exponen-tial function (e.g., Paulson and Simpson, 1977) consider-ing only the simple classification of water type (e.g.,Jerlov, 1968) is convenient and is often used to calculatethe downward shortwave radiation flux in seawater. How-ever, this parameterization is not always satisfactory (e.g.,Sui et al., 1997b), and cannot consider the interactionbetween physical and biological processes. Recently asignificantly improved parameterization that depends onupper-ocean chlorophyll-a concentration, cloud amount,and solar zenith angle has been proposed (Ohlmann andSiegel, 2000). Fairall et al. (1996) originally adoptedshortwave-radiation parameterizations that depended ononly depth for their skin-layer and warm-layer models.Ohlmann and Siegel (2000) and Wick et al. (2005) re-placed them with Ohlmann and Siegel’s parameterization,and compared the temperature and surface fluxes simu-lated by this modified version of Fairall et al.’s modelwith those by the original model. If Ohlmann and Siegel’sparameterization is adopted, due to the reduction of theabsorption of insolation, the skin effect is strengthenedand the temperature difference across the warm layer isdecreased. As a result, SSTskin and the net heat flux fromthe ocean can be reduced by about 0.2 K and 5 Wm–1

under calm and clear conditions, respectively.As reviewed here, use of an improved

parameterization for shortwave radiation in the ocean isimportant to simulate SST and surface fluxes in a numeri-cal model accurately. It is known that biological proc-


esses such as increase of phytoplankton and cyanobacteriacan significantly affect SST (e.g., Kahru et al., 1993).Siegel et al. (1995) found that in the warm pool duringCOARE, the penetration depth of shortwave radiationdecreased substantially after westerly bursts. This was dueto the upward mixing of nutrients and subsequentphytoplankton growth. Godfrey et al. (1998) suggestedthat plankton dynamics may have a significant influenceon SST in the warm pool too. It has also been reportedthat the chlorophyll-a concentration in the upper oceansignificantly increases in response to tropical cyclones(e.g., Subrahmanyam et al., 2002; Siswanto et al., 2007).The formula proposed by Ohlmann and Siegel will beuseful when considering the physical-biological interac-tion in relation to air-sea interaction.c. Time step and vertical resolution

Restricted computational resources make it suffi-ciently difficult to refine the temporal and vertical reso-lution of an OGCM so that a sharp diurnal thermoclinecan be reproduced. Although even a model with a coarsevertical resolution of 10–15 m in the upper ocean cansimulate the diurnal variation to a certain degree (Schillerand Godfrey, 2003; Danabasoglu et al., 2006), more real-istic simulations need a much finer vertical resolution inthe upper ocean. Bernie et al. (2005) discussed the tem-poral resolution of forcing flux and the vertical resolu-tion required to accurately reproduce the diurnal varia-tion of SST by a numerical model. They indicated that atemporal resolution of less than 3 h and a vertical resolu-tion of less than 1 m should be specified in order to re-produce more than 90% of the amplitude of the diurnalSST variation.d. Other model parameterizations

Modeling methodology remains affected by otherproblems, one of which is uncertainty in the bulk coeffi-cients used to estimate air-sea fluxes (e.g., Clayson andChen, 2002). Another is concerned with schemes of anatmospheric model. A coupled GCM (CGCM) with a shortcoupling interval of 1–3 h between an atmospheric GCMand an OGCM can produce diurnal ocean variations(Danabasoglu et al., 2006). However, even if correct di-urnal SSTskin variations are supplied to an atmosphericmodel as a lower boundary condition, the model atmos-phere cannot correctly respond to the diurnal variationsof SSTskin without appropriate parameterizations. PresentCGCMs still have deficiencies in the dynamics for low-level atmospheric convergence and in their physicalparameterizations for the planetary boundary layer, cloudand precipitation formation, moist convection—especiallyat its initiation, as well as the deficiency that simulateddiurnal SST variations are too small (Dai and Trenberth,2004). These atmospheric parameterizations also need tobe improved in order to study air-sea interaction on a di-urnal time scale.

Fig. 16. (a) Sample SST and (b) turbulent boundary layer depthtime series from the control integration with hourly fluxes(Run CTL, solid line), and the sensitivity experiment withdaily mean fluxes (Run 24HR, dotted line). IMET buoy dataat 2°S, 156°E during COARE and a one-dimensional mixedlayer model were used for the simulations. Dashed lineshows the daily mean SST from the control integration toemphasize the intraseasonal variability. Reproduced fromBernie et al. (2005).

7.2 ObservationsSatellite observations, especially by such microwave

sensors as TMI and AMSR-E, are very effective, indeedindispensable for research into high-frequency SST vari-ation. In order to resolve the global diurnal cycle, flightsof at least two satellites with microwave sensors are de-sirable. High-quality, sustainable satellite observationsmust be continued.

However, uncertainty in satellite-derived SST is una-voidable. High-quality, continuous in situ observationsof near-surface temperature are also necessary in orderto minimize satellite SST errors and to determine the ver-tical temperature profile. At present moored buoys aredensely arranged only in the tropics and some coastal ar-eas. As mentioned above, the diurnal variability of SSTwill be also important in the extratropics, and we need adense in situ observation system to observe the diurnalchange of the upper ocean even in the mid- and high-latitudes.

In situ SST measurement also has some problems.For ship SST data, it is well known that the SSTs reportedfrom voluntary observing ships are noisier than buoySSTs, and can have a warm bias due to the heating in theengine room (e.g., Saur, 1963; Reynolds and Smith, 1994;Emery et al., 2001; Reynolds et al., 2002). The SSTs ob-served with buoys are usually considered to be more reli-able, and are utilized for the tuning and validation of sat-


ellite SSTs. However, Kawai and Kawamura (2000) andKawai et al. (2006b) indicated that the temperature ob-served with a moored buoy at about 1-m depth woulddeviate from the actual temperature at the nominal depthwhen a sharp diurnal thermocline develops just near thesurface. Although the exact reason for this still remainsunclear, the turbulence and/or heating induced by a buoyhull are suspected.

A careful temperature measurement technique thatavoids disturbing the near-surface temperature field is re-quired when a sharp diurnal thermocline is formed. Oneof the solutions is use of a compact profiling float. Wardand Minnett (2001) and Ward et al. (2004b) developedthe SkinDeEP autonomous profiler, which can measurenear-surface temperature with a fine vertical resolutionwithout disturbance. SkinDeEP is similar to an Argo-typefloat, but it is smaller and its temperature sensors pro-trude several tens of centimeters from the top of the bodyto avoid distorting the stratification. Although this floatis excellent in near-surface temperature measurement,only a few prototypes have been built and they are notequipped with telecommunication functionality. Atpresent, many profiling floats are deployed globally un-der the international cooperation of the Argo Project (e.g.,Argo Science Team, 2001; Argo Project Office, 2006),but the normal profiling floats do not measure the sur-face layer above about 5-m depth in order to prevent deg-radation of sensor performance caused by contaminantsnear the sea surface, such as oil (e.g., Kobayashi et al.,2004; Riser and Wijffels, 2005). If the profiling floatsare improved to measure near-surface temperature withfine vertical and temporal resolution, this will become apowerful tool for studies on the diurnal SST variability.

8. SummaryThe importance of the diurnal variability of SST is

becoming increasingly clearly recognized. This paper hassummarized studies of the diurnal SST variation and itspossible impacts on air-sea interaction. We first introducedthe latest definitions of the several kinds of “SST” (Sec-tion 2), and reviewed the observational facts about thediurnal SST variation (Section 3). Basically, when inso-lation is strong and wind speed is low, the diurnal rise ofSST becomes large. Early studies indicated that the diur-nal amplitude of SSTdepth was 0.2–0.6 K in the low andmid latitudes on average, reaching about 1.5 K under clearand calm conditions. Studies conducted during the pasttwo decades have revealed from in situ and satellite ob-servations that the diurnal rise of SSTskin or SSTsubskin canreach 5 K or more in extreme cases. Satellite observationalso clarified that the large diurnal rise can occur overwide areas in a specific season. Various kinds of modelhave been proposed and utilized to simulate diurnal vari-ations in the upper ocean (Section 4). The large diurnal

SST variation can be approximately simulated by themodels, although there still remain some challenges inprecise modeling.

The atmosphere feels SSTskin, not SSTdepth, throughsurface heat fluxes. Hence the estimations of air-sea heatand gas fluxes are susceptible to the diurnal SST vari-ability and the skin effect. Previous studies of the surfaceflux estimations were then summarized (Section 5). Whilethe cool skin layer almost always exists through a day,even in windy conditions, the warm layer is formed onlyin the daytime of a calm and clear day. Therefore, theskin effect may be more important for the flux estimationthan the effect of the warm layer. However, for the heatflux, it is indicated that the consideration of the warmlayer can increase the net heat flux by 50–60 W m–2 inthe daytime, and its temporal mean exceeds 10 W m–2.Furthermore, the significant effect of the skin layer andthe warm layer on air-sea gas exchange has already beenpointed out, and the surface mixing process on the diur-nal scale can also affect marine biology (McCreary et al.,2001). Accurate physical-chemical-biological modelingand material circulation studies will need knowledge ofthe ocean’s diurnal variability.

Recent studies of the relation between the diurnalSST variation and air-sea interaction were then introduced(Section 6). Whether the diurnal SST variation really af-fects the atmospheric physics significantly is a difficultbut interesting question. A few studies have showed thatthe diurnal variation and/or the skin effect can modifyprecipitation and surface fluxes variations on anintraseasonal scale, the vertical profile of the air tempera-ture and humidity, and a sea-breeze circulation. Althoughat present the investigation of this subject is not yet ad-equate, many researchers expect that the diurnal cycle inSST will have some impact on the atmosphere, and anattempt to simulate the diurnal variation of the upperocean in a GCM has already begun. The necessity of thisattempt at a numerical model has also summarized (Sub-section 7.1). Fine vertical/temporal resolution and appro-priate parameterization for shortwave extinction in theocean are required to accurately simulate large diurnalSST rise. Some schemes that enable us to reproduce real-istic diurnal SST variations without enormous computa-tional load have been proposed recently (e.g., Schiller andGodfrey, 2005; Zeng and Beljaars, 2005).

In conclusion, the issues to be clarified can be sum-marized as follows:

(1) A few studies have pointed out from numericalexperiments that the diurnal SST variation and/or the skineffect can significantly affect the atmospheric field overthe warm pool (e.g., Li et al., 2001; Clayson and Chen,2002). However, the processes through which the differ-ences in cloudiness and humidity were caused were notdiscussed, and still remain unknown.


(2) The diurnal temperature rise and the tempera-ture drop across the skin layer increase or decrease theair-sea sensible heat flux, and thus will affect the heatcontent and height of the atmospheric boundary layer. Theperturbation of only a few W m–2 of the sensible heat flux,which will be negligible for the ocean, may significantlyaffect the lower atmosphere. The changes of the atmos-pheric mixed layer and the surface wind field related withthe diurnal SST variation need to be investigated inten-sively. Furthermore, whether large diurnal SST rise re-ally can be the trigger for the shallow cumulus convec-tion (Slingo et al., 2003), which may control the precon-ditioning of the MJO active phase, has not been confirmedyet, either.

(3) The effect of the diurnal SST rise on a coastallocal atmospheric circulation has been indicated by Kawaiet al. (2006a). They reported only an idealized calm andclear case. More detailed numerical experiments are nec-essary for more realistic conditions and/or different ar-eas, especially for the tropics. Consideration of this ef-fect may be significant for practical weather forecastingin coastal regions.

(4) While many researchers interested in the diur-nal SST variation pay much attention to the tropics andsubtropics, the diurnal variation in the high latitudes hasrarely been noted. However, as shown in Fig. 5, the diur-nal SST rise can become large even in the high latitudesin summer. In situ observations that can resolve the diur-nal SST cycle are not sufficiently close to the polar re-gions. Intensive studies focusing on the high latitudesshould be conducted.

(5) As mentioned in Subsection 7.1.d, someparameterizations in an atmospheric model would not beappropriate for simulating atmospheric response to thediurnal SST variation. Further improvement of the modelparameterizations will be necessary.

(6) When a sharp and shallow diurnal thermoclineis formed, in situ near-surface temperature measurementis not easy (Subsection 7.2). Careful measurements with-out instrument-induced turbulence and/or heating are re-quired for studies of diurnal air-sea interaction.

Again, the impact of the diurnal SST variability onair-sea interaction has not yet been investigated suffi-ciently. Even if the diurnal change of SST itself were tohave little effect on the atmosphere, it has been confirmedthat the formation/decay process of the diurnalthermocline near the surface cannot be neglected in or-der to reproduce the SST variation on an intraseasonal orlonger scale accurately in a model, which is essential toair-sea interaction, especially in the tropics. Further stud-ies using numerical models are necessary, and an observ-ing system that can detect the diurnal cycle in SST allover the world is also indispensable for the corroborationof the model simulation.

AcknowledgementsThe authors would like to greatly thank C. J. Donlon,

H. Kawamura, G. A. Wick and all the members of TheGHRSST-PP Science Team, K. Yoneyama, K. Ando, M.Katsumata, T. Kobayashi of JAMSTEC, J. Ishizaka ofNagasaki University, and T. Shimada and H. Qin ofTohoku University for providing us with useful informa-tion and support. We also appreciate valuable commentsof two anonymous reviewers. The AMSR-E data used inthis paper are produced by Remote Sensing Systems andsponsored by the NASA Earth Science REASoNDISCOVER Project and the AMSR-E Science Team. Thedata are available at [www.remss.com].

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