Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas

Journal of Oceanography, Vol. 55, pp. 257 to 270. 1999 Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas JUNGYUL NA 1, JANGWON SEO 2 and HEUNG-JAE LIE 3 1 Department of Earth & Marine Sciences, Hanyang University, 1271 sa-1-dong Ansan 425-791, Korea 2 Marine Meteorology Research Laboratory, Meteorological Research Institute, Korea Meteorological Administration, 110-360, Korea 3 Physical Oceanography Division, Korea Ocean Research and Development Institute, P.O. Box 29, Ansan 425-600, Korea (Received 13 October 1998; in revised form 5 December 1998; accepted 10 December 1998) Based on the twice-daily marine atmospheric variables which were derived mostly from the weather maps for 18 years period from 1978 to 1995, the surface heat flux over the East Asian marginal seas was calculated at 0.5 0.5 grid points twice a day. The annual mean distribution of the net heat flux shows that the maximum heat loss occurs in the central part of the Yellow Sea, along the Kuroshio axis and along the west coast of the northern Japanese islands. The area off Vladivostok turned out to be a heat-losing region, however, on the average, the amount of heat loss is minimum over the study area and the estuary of the Yangtze River also appears as a region of the minimum heat loss. The seasonal variations of heat flux show that the period of heat gain is longest in the Yellow Sea, and the maximum heat gain occurs in June. The maximum heat loss occurs in January over the study area, except the Yellow Sea where the heat loss is maximum in December. The annual mean value of the net heat flux in the East/Japan Sea is 108 W/m 2 which is about twice the value of Hirose et al. (1996) or about 30% higher than Kato and Asai (1983). For the Yellow Sea, it is about 89 W/m 2 and it becomes 75 W/m 2 in the East China Sea. This increase in values of the net heat flux comes mostly from the turbulent fluxes which are strongly dependent on the wind speed, which fluctuates largely during the winter season. Keywords: Surface heat flux, net heat flux, Yellow Sea, East/Japan Sea, East China Sea, monthly and annual means. 1. Introduction The sparsity of observation data in time and space over the East Asian marginal seas has forced one to use climatological means or statistical methods to obtain information of the surface heat flux. Furthermore, most of the studies on the heat budget is limited to the East/Japan Sea area (Miyazaki, 1952; Aldoshina, 1957; Leonov et al., 1961; MMO, 1972; Shim and Kim, 1981; Kato and Asai, 1983; Kim, 1992; Kang et al., 1994; Kim and Kang, 1995; Park et al., 1995; Hirose et al., 1996) due to the relative abundance of observations. Equivalent informations of the sea surface flux over the East/Japan Sea are limited in numbers reported over the Yellow and East China Seas (Sakurai et al., 1989; Kim, 1992; Hirose, 1995). Even the climatological means of each component of the surface heat fluxes over the East/Japan Sea have been estimated by various scientists, the heat fluxes are significantly different because of the different bulk schemes and data sets. For example, Hirose et al. (1996) compared the seasonal and annual mean values of the sensible and latent heat fluxes in the East/Japan Sea estimated by many scientists. Most significant difference between the individual studies occurred for the winter season with 44 W/m 2 of the sensible heat flux and 46 W/m 2 of the latent heat flux. But the maximum difference between the various estimations during the summer season was 7 W/m 2 in the sensible heat flux and 18 W/m 2 in the latent heat flux. It has been known that the estimated values of heat flux are dependent on (1) the bulk formulas used to calculate the heat flux, (2) the type of data acquisitions and (3) the spatial and temporal resolution of the data set (Hsiung, 1986). In fact, Clark (1967) found that the long-term mean net heat flux calculated from individual observations resulted in as large as 20% increase over the fluxes calculated from monthly mean meteorological variables. Over the East/ Japan Sea, Kato and Asai (1983) and Kawamura and Wu (1998) used twice-daily meteorological variables, and their values of the surface heat fluxes were larger than the previous estimations based on the climatological data. The importance of using 12-hourly data rather than the smoothed monthly values was emphasized by Stanev (1994) in terms of less heat transfer between the atmosphere and the ocean when Copyright The Oceanographic Society of Japan. 257

Fig. 1. Spatial distribution of the 18-years monthly mean of net heat flux (in W/m 2 ). Negative value indicates the heat flux upward from the sea to the atmosphere. 258 J. Na et al.

Fig. 1. (continued). Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 259

the atmospheric data were low-pass filtered to eliminate the synoptic variability. However, unless evenly distributed observation data in space and time are available, the bulk schemes and the type of data sets are always subjected to arguments. In an effort to obtain the sea-surface wind field in the adjacent seas around the Korean peninsula, Na et al. (1992) calculated 12-hourly wind stress and wind stress curl by applying the Cardone (1969) model to twice-daily weather charts. The data set used to calculate the wind speed at 1/2 1/2 grid points was derived from direct reading of the parameters from the weather chart. Thus, relatively consistent distribution of data in time and space was obtained over the period of 1978 1987 and for the present study the data length has been extended to 1978 1995. Since many numerical studies (Seung and Yoon, 1995; Kim and Yoon, 1996) were done by using the wind data of Na et al. (1992) to reproduce the observational phenomena in the East/Japan Sea, it is very plausible to calculate surface heat flux based on the same data set, together with other parameters such as cloudiness and specific humidity which are also available from the weather charts. The purpose of this study is two-folded. One is to establish time-series (12-hourly) data set and the other is to calculate seasonal variations of the surface heat fluxes over the East Asian marginal seas. In the following section, the data set and the bulk formulas are explained and the monthly and annual mean heat fluxes are followed by the discussions and the summary. 2. Database and Calculation of Heat Fluxes 2.1 Data set The data set used for this study is mostly derived from the twice-daily printed weather maps by JMA (Japan Meteorological Agency) and station data from KMA (Korea Meteorological Administration) for the period from 1978 to 1995. The spatial coverage of this study is 20 to 50 N and 120 to 150 E. In order to obtain the climatological components for estimation of heat flux, air temperature, pressure, cloudiness and specific humidity were read from the weather maps and supplemented by the KMA station data. For the sea surface winds, the Cardone (1969) model has been used with the JMA ten-day mean sea surface temperature charts. In this way, homogeneously distributed data set both in time and space is established for the calculation of the heat fluxes over the East Asian marginal seas. Thus, a high frequency data set with an interval of 12 hours is obtained at 1/2 1/2 grid points and it amounts more than 13000 data at each point for the period of 18 years. In particular, the amount of cloud at each grid point over the open sea is evaluated by considering the movement of weather pattern that includes the fronts as well as the cloud patches from the weather maps. Thus, this data set could reduce random errors associated with sampling bias from inadequate samples such as uneven sampling in time and concentrated sampling in space. 2.2 Calculation of 12-hourly heat fluxes The net heat flux at the sea surface (Q N ) is given as Q N = Q S (Q L + Q H + Q E ) (1) where Q S and Q L are the solar and long-wave radiation flux, Q H and Q E are the sensible and latent heat fluxes, respectively. The solar radiation flux (Q S ) is estimated by Q S = Q o (0.865 0.5C 2 )(1 α s ) (2) where Q o is the solar radiation under clean sky (Seckel and Beaudry, 1973), C is the amount of cloud in tenths, α s is the albedo at the sea surface (=0.06). The long-wave radiation flux (Q L ) is calculated according to the formula (Clark et al. 1974) Q L =εσt S 4 (0.39 0.00495e a 0.5 )(1 δc) + 4εσT S 3 (T s T a ) (3) where ε is the emissivity of water (=0.97), σ is the Stefan- Boltzman constant (=5.6705 10 8 W/m 2 K 2 ), δ is the cloud coefficient which is a function of latitude and it is varying from 1.0 at the poles to 0.5 at the equator (Berliand and Berliand, 1952) and e a is the vapor pressure, and T s and T a are the sea surface and air temperature, respectively. Twice-daily values of the latent (Q E ) and sensible (Q H ) heat fluxes are estimated by the bulk formulas with Kondo s transfer coefficients (1975) as follows: Q H = ρc p C H u(t s T a ), (4) Q E = ρl v C E u(q s q a ). (5) In Eqs. (4) and (5), ρ is the air density, C p is the specific heat of air at constant pressure, u is the wind speed, L v is the latent heat of evaporation, q a is the specific humidity and q s is the saturated specific humidity at T s. C H and C E are the transfer coefficients for the sensible and latent heat flux, respectively. 3. Surface Heat Flux over the East Asian Marginal Seas 3.1 Monthly and annual means The monthly mean values of surface heat flux are obtained from the 12-hourly computation of heat flux at each grid point, that is, the mean value at a grid point corresponds to the time mean of at least 1080 flux data. In order to see the seasonal variations of each component of the sea surface heat fluxes, except the net heat flux (Q N ) of every 260 J. Na et al.

month, the representative month for each season (January, April, July and October) is selected and the results are presented in Figs. 1 through 5. Figure 1 shows the 18-years monthly mean of net heat flux at the sea surface. From September to March, the East Asian marginal seas is losing heat into the atmosphere, i.e., Q N is negative. The largest heat loss appears in the month of January and the maximum value of more than 400 W/m 2 occurs along the Kuroshio axis and in the central part of the Yellow Sea. Also, the northwestern and central parts of the East/Japan Sea attain the maximum heat loss in January. It is interesting to note that the regions with the smallest heat loss during the period from November to March are the area near Vladivostok, the western coast of central Japan (Honshu) and at the mouth of Yangtze River. The pattern of spatial distribution of the net heat flux seems to follow that of the latent and the sensible heat flux (Figs. 4(a) and 5(a)) especially for the winter season. In the Korea Strait, the largest heat loss occurs from September to November and the magnitude of Q N is almost equivalent to the maximum values appeared in the East/Japan Sea. In April, the spatial pattern changes considerably. The only significant heat loss regions are remaining in the northeastern part of the East/Japan Sea, in the Korea Strait and along the Kuroshio axis. Meanwhile, the whole part of the Yellow Sea and the northern half of the East/Japan Sea centered near Vladivostok start gaining heat energy. In fact, very similar pattern of the heat flux distribution can be seen in April for the latent and the sensible heat flux as well as the longwave radiation (Figs. 3(b), 4(b) and 5(b)). In May, the Fig. 2. Monthly mean solar radiation, Q S in W/m 2, in January (a), April (b), July (c) and October (d). Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 261

region of heat loss is confined to the Kuroshio axis with the values of slightly lower than zero. The largest gain of heat occurs during June and July. The areas near Vladivostok and Shantung peninsula attain more than 160 W/m 2 in June, however in the area off Vladivostok the maximum values of Q N remains in July. The month of August seems to appear as a transitional period of the net heat flux in the East Asian marginal seas. In the Yellow and East China Seas, the values of Q N with slightly less than zero appear over the most part. But in the East/Japan Sea, except the west coastal regions centered around the Tsugaru Strait, where Q N becomes nearly zero, most part of the sea maintains positive Q N. The general pattern of the net heat flux over the study area shows that the Yellow Sea gains heat during the four months (April to July) and the northern part of the East/Japan Sea, especially off Vladivostok, gains heat for five months period (April to August). The 18-year annual mean of each heat flux components is shown in Fig. 6. The annual mean distribution of the net heat flux (Fig. 6(a)) shows that the larger heat loss occurs at three distinct regions; the central part of the Yellow Sea, the northwestern coastal region of Japanese islands and the region along the Kuroshio axis. The smallest heat loss appears in the area near Vladivostok and at the mouth of the Yangtze River with the magnitude of 40 W/m 2. The pattern of the annual mean distribution of the net heat flux is very similar to those of the latent (Fig. 6(d)) and the sensible (Fig. 6(e)) heat flux. The region of a maximum sensible or latent heat loss also corresponds to the area of large net heat loss, and this tendency is also true for the region of the least heat Fig. 3. Monthly mean long-wave radiation, Q L in W/m 2, in January (a), April (b), July (c) and October (d). 262 J. Na et al.

loss. However the latent heat flux is dominant over the sensible heat flux which is the smallest component among the heat flux terms and the spatial distribution of the net heat flux follows the pattern of the latent heat flux which is strongly dependent on the factors like wind speed and the air-sea temperature difference. The seasonal variation of the heat fluxes, which are the spatially averaged monthly mean of each component of the flux, are presented for the East/Japan Sea (Fig. 7(a)), the Yellow Sea (Fig. 7(b)) and the East China Sea (Fig. 7(c)), respectively. The period of heat gain in the Yellow Sea is the longest among them and the maximum heat-gain occurs in June for all the seas. The month of the maximum heat-loss is January in the East/Japan Sea and in the East China Sea, but it is December in the Yellow Sea. The maximum value of the latent heat flux appears in September in the Yellow Sea and the East China Sea. However, the East/Japan Sea has its maximum in February. The annual mean values of the net heat flux of the East/Japan Sea is about 108 W/m 2 which is twice the value of Hirose et al. (1996) or about 30% higher than Kato and Asai (1983). These discrepancies may be due to the difference in time resolution of the data sets, and it will be discussed further in the next section. For the Yellow Sea, the mean value is about 89 W/m 2 and it becomes 75 W/m 2 in the East China Sea. Therefore, all the marginal seas are losing heat from the sea surface. 3.2 Discussions It is a difficult task to compare the present estimation of the various heat flux components with the previous studies, Fig. 4. Monthly mean latent heat flux, Q E in W/m 2, in January (a), April (b), July (c) and October (d). Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 263

since (1) the spatial or the temporal resolution of the data sets is different, (2) the different bulk formulas are used to calculate the fluxes and (3) the coverage of study areas is not identical. Therefore, we will restrict our comparisons to those estimates that have similar coverage of area or similar method of computation in terms of the bulk formula and the amount of data. Kang et al. (1994) obtained the seasonal variations of the surface heat flux at 2 2 grid points over the seas whose area extent was almost identical with the present study. However, even they used daily meteorological data (pressure, temperature and specific humidity) from the ECMWF (European Center for Medium Range Forecast) for three-year period from 1984 to 1987, the method of computing the heat fluxes by using a flux model is different from this study. Meanwhile, Hirose (1995) estimated the surface heat flux over the area between 23 N and 53 N in latitude, and between 117 E and 143 E in longitude with 1 1 resolution for the period of 31 years from 1960 to 1990, by the bulk method using all available vessel data. The area and the bulk formulas of Hirose (1995) are, therefore, very much similar to ours except the data set. Another estimation similar to that of Hirose (1995) was done by Kim (1992) but with 2 2 resolution and monthly averaged meteorological parameters. The annual mean distribution of the net heat flux (Fig. 6(a)) shows a good agreement with the previous studies (Kim, 1992; Kang et al., 1994; Hirose, 1995) over the area around the Kuroshio axis and also over the East China Sea. However, large discrepancies exist in the Yellow Sea and especially in the northern part of the East/Japan Sea, in terms of magnitude and spatial distribution. Fig. 5. Monthly mean sensible heat flux, Q H in W/m 2, in January (a), April (b), July (c) and October (d). 264 J. Na et al.

Fig. 6. Annual mean distribution of each heat flux component in W/m 2, Net heat flux (a), Solar radiation (b), Long-wave radiation (c), Latent heat flux (d) and Sensible heat flux (e). Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 265

Fig. 7. The 18-year mean seasonal variation of the monthly mean fluxes over the East/Japan Sea (a), the Yellow Sea (b) and the East China Sea (c). In Yellow Sea, Kim (1992) and Hirose (1995) show positive values of Q N with 0~20 W/m 2, but our estimation of Q N is negative with the maximum value of 140 W/m 2 at the central part of the Yellow Sea. This discrepancy may be due to the difference in data sets. For example, the long-term mean air temperature distribution in January of Hirose (1995) shows that, over the central part of the Yellow Sea, it is about 3 C which is about 4 C warmer than ours. Furthermore the fact that our wind speed is large by 50% in magnitude and the sea surface temperature is almost the same, could produce a big discrepancy in the latent and sensible fluxes between two studies. In the northern part of the East/Japan Sea, where the number of vessel data is relatively small but larger than the Yellow Sea (Hirose, 1995), the annual mean of Q N estimated by Hirose et al. (1996) and Kim (1992) agree well with our results in terms of spatial distribution of large heat loss, however, our value is higher by 50% in magnitude than theirs. In the area near Vladivostok, our results show net heat loss ( 40 W/m 2 ), while they show a tendency of small amount of heat gain. As for the monthly mean distributions of heat flux in the East/Japan Sea, our period of heat-loss season during September to March agrees well with Hirose et al. (1996). But, significant discrepancies exist in the area off Vladivostok in the months of March and September such that our results of heat-loss are different from their heat-gain in the same months. This means that the area off Vladivostok gains more heat according to the results by Hirose et al. (1996) than the present study, and the consequences of the results are reflected in the distributions of Q N (Fig. 1). Another difference in terms of seasonal distribution of the region of large heat loss is the central part of the East/ Japan Sea during the winter season (December to February). In winter, we have relatively large heat loss appeared over the central part of the sea with more than 400 W/m 2 which is larger than any other previous calculations over that region, except Kato and Asai (1983) who obtained 350~ 400 W/m 2 for the winter season. Since the latent heat flux is used to be a dominant component among the heat fluxes in the East/Japan Sea, a comparison is made between two annual mean distributions of the latent heat flux by Hirose (1995) and the present study (Fig. 8). As expected, our result is greater in the northern part of the East/Japan Sea by 40 W/m 2 in magnitude. In an effort to find the reason for this discrepancy in magnitude, we calculated two different means of the latent heat flux for the month of January 1994. Background of the selection of January is because of the frequent events of the cold-air outbreak are taking places (Na et al., 1992) and also the effects of stronger wind fields may be reflected by the bulk formula that is dependent on the wind speed. Then, one was calculated using the 12-hourly atmospheric variables (Fig. 9(a)), and the other was calculated using the monthly averaged variables (Fig. 9(b)). In the northern part of both the East/Japan Sea and the Yellow Sea, 266 J. Na et al.

Fig. 8. Annual mean distributions of the latent heat flux calculated by Hirose et al. (1996) (a) and our result (b) showing a significant difference over the northern part of the East/Japan Sea. Fig. 9. The distribution of latent heat flux in January, 1994, calculated from 12-hourly data set (a) and from monthly averaged data (b). Use of the monthly averaged data results in 50% reduction in the northern part of the East/Japan Sea and the Yellow Sea. that the magnitude of the latent heat flux calculated from the averaged values is reduced by 50%. This fact may explain why our results of the heat flux are greater in magnitude than the previous studies that were based on either the climatological mean values of the marine meteorological parameters (MMO, 1972: Park et al., 1995) or the temporally inhomogeneous data set (Hirose, 1995). Recently, using twice-daily ECMWF data set with the mean wind field obtained by the NASA scatterometer (NSCAT) over the East/Japan Sea in January 1997, Kawamura and Wu (1998) calculated the monthly mean sensible and latent heat fluxes to identify the area south of Vladivostok as the center of deep convection. Their results show that the turbulent heat flux reaches to the amount of more than 300 W/m 2 off Vladivostok and over the most part of south of the polar fronts. Kato and Asai (1983) also showed that the magnitude of sensible and latent heat fluxes could increase by 20 W/m 2 in the northern part of the East/ Japan sea by using the daily values. In a numerical study on the water mass formation in Black Sea in winter by Stanev (1994), it has been pointed out that the filtering of high frequency atmospheric data caused a severe reduction of Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 267

Fig. 10. Long-term seasonal variations of the latent and the sensible fluxes (a), the solar and the long-wave radiation and the net heat flux (b) in the East/Japan Sea. heat transfer to atmosphere. Even in the 12-hourly variations of 18-year mean of the heat fluxes averaged over the East/Japan Sea, shown in Fig. 10, large amplitude fluctuations of the sensible and latent heat fluxes in the winter season are clearly seen. Since due to a lack of temporally homogeneous observations, the usefulness or validity of using a high frequency data set may still remain as a future work for verification. As for the use of ship observations for the heat flux estimation, it should be pointed out that the air temperatures observed by ship in winter season are generally higher than the one observed at the buoy by 2.5 C (Park et al., 1995) and this eventually reduced the net heat flux by 50 W/m 2 in February. Furthermore, the short-term variability of wind speed observed in January, 1994 at the JMA buoy 6 caused both the temperature difference between the air and the water by amounts of 13 C and the humidity difference as well (Fig. 11) because of the cold northerly winds. It is interesting to note that the region with the large standard deviation of the annual mean net heat flux corresponds to the region of large net heat loss (Fig. 12) and this may reflect that the area is influenced by the temporal variability of the synoptic weather patterns (Han et al., 1995; Na et al., 1997). 4. Summary and Conclusion Based on the twice-daily marine atmospheric variables which were derived mostly from the weather maps for 18 years period from 1978 to 1995, the surface heat flux over 268 J. Na et al.

Fig. 11. Time series of wind speed, the air-sea temperature difference and the specific humidity difference observed at the JMA buoy 6 in January 1994. Fig. 12. Standard deviation of the annual mean of the net heat flux (in W/m 2 ). the East Asian marginal seas was calculated at 1/2 1/2 grid points twice a day. The data set, therefore, could make one to avoid the problems of systematic and random errors associated with inhomogeneous distribution of data sampling both in space and in time. Use of the daily values (Kato and Asai, 1983; Kang et al., 1994; Kawamura and Wu, 1998) resulted in an increase in the mean net heat flux as compared with the fluxes from averaged variables (Kim, 1992; Park et al., 1995). Clark (1967) and Hsiung (1986) estimated the increase by 10% to 20% in the net heat flux over the calculation of the fluxes from averaged values. The major contribution of this increase comes from the sensible and the latent heat fluxes which are strongly dependent on the wind speed, which fluctuates largely in time, especially in the winter season (Fig. 10). Thus, use of averaged variables or filtering high frequency atmospheric data could result in a severe reduction of cooling during the winter season (Stanev, 1994). The annual mean distribution of Q N shows that the maximum heat loss occurs in the central part of the Yellow Sea, along the Kuroshio axis and along the west coast of the northern Japan. This agrees well with Hirose (1995) in terms of the location but not in magnitude. In particular, the area off Vladivostok turned out to be a heat-losing region from our result, while it was the region of heat-gain of a small amount from Hirose et al. (1996). However, on the average, the area off Vladivostok and the area near the mouth of Yangtze River appear as the area of minimum heat loss. The seasonal variations of heat flux over the East Asian marginal seas show that the period of heat gain in the Yellow Sea is the longest among them and the maximum heat gain occurs in June for all the Seas. Also, the maximum heat loss occurs in January in the East/Japan Sea and the East China Sea, but it is December in the Yellow Sea. The annual mean values of the net heat flux shows that the East Asian Marginal Seas are losing heat on the average and it is about 108 W/m 2 in the East/Japan Sea which is about twice the values of Hirose et al. (1996) or about 30% higher than Kato and Asai (1983). For the Yellow Sea, the mean value of Q N is about 89 W/m 2 and it becomes 75 W/m 2 in the East China Sea. For the Yellow Sea, the mean value of Q N is about 89 W/m 2 which is the largest among the previous estimations (Ishii and Kondo, 1987; Kim, 1992; Hirose, 1995). Hirose (1995) and Kim (1992) esti- Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas 269

mated Q N to be 10 W/m 2, while Ishii and Kondo (1987) suggested 11 W/m 2. These differences may be due to lack of observations, which have been emphasized especially over the Yellow Sea. However, our value of Q N, 75 W/m 2, over the East China Sea is exactly same value estimated by Kurasawa et al. (1983) and Sakurai et al. (1989). Ishii and Kondo (1987) s estimation is 80 W/m 2 and Hirose (1995) s value is 90 W/m 2. Therefore, even though they used different bulk formulas, the heat flux estimation over the area where homogeneously distributed observations are available produces very similar results. In conclusion, the present study has taken advantage of the temporal and the spatial homogeneity of the high frequency sea surface flux data sampled at an 12-hour interval, and from the analysis of this data set, the magnitude of the heat fluxes is estimated to be larger than that of the previous studies, so that on the average, the East Asian marginal seas are losing heat to the atmosphere much more than the previous estimations. Acknowledgements This work was supported by the Ocean Research Institute Program of the Korea Ministry of Education for Jungyul Na and by the Korea Ministry of Science and Technology for Heung-Jae Lie. Jangwon Seo acknowledges the support for Special Research Project by the Korea Ministry of Science and Technology. References Aldoshina, E. I. (1957): Heat budget at the Japan Sea surface. Selected papers of Geophys., 12, 411 442 (in Russian). Berliand, M. E. and T. G. Berliand (1952): Determining the net long-wave radiation of the earth with consideration of the effect of cloudiness. Izv. Akad. Nauk. SSSR Ser. Geofiz., No. 1, 64 78. Cardone, V. J. (1969): Specification of the wind distribution in the marine boundary layer for wave forecasting. New York Univ. School of Eng. and Sci. Rep. GSL-TR-69-1, 181 pp. Clark, N. E. (1967): Large-scale heat transfer processes and fluctuations of sea surface temperature in the North Pacific Ocean. Ph.D. Thesis, Dep. of Meteor., Mass. Inst. of Technol., Cambridge, 148 pp. Clark, N. E., L. Eber, R. Laurs, J. Renner and J. Saur (1974): Heat exchange between ocean and atmosphere in the eastern North Pacific for 1961 71. NOAA Tech. Rep. NMFSSSRF-682. Han, S. K., H.-J. Lie and J. Y. Na (1995): Temporal and spatial characteristics of surface winds over the adjacent seas of the Korean Peninsula. J. Oceanol. Soc. Korea, 30, 550 564. Hirose, N. (1995): Heat budget in the neighboring seas around Japan. Master s Thesis, Kyushu Univ., 142 pp. Hirose, N., C. H. Kim and J. H. Yoon (1996): Heat Budget in the Japan Sea. J. Oceanogr., 52, 553 574. Hsiung, J. (1986): Mean surface energy fluxes over the global ocean. J. Geophys. Res., 91, 10585 10606. Ishii, T. and J. Kondo (1987): Seasonal variation of the heat balance of the East China Sea. Tenki, 34, 517 526. Kang, I. S., M. K. Kim and T. B. Shim (1994): Seasonal variation of surface heat budget and wind stress over the seas around Korean Peninsula. J. Oceanol. Soc. Korea, 29, 325 337. Kato, K. and T. Asai (1983): Seasonal variations of heat budgets in both the atmosphere and the sea in the Japan Sea area. J. Meteor. Soc. Japan, 61, 222 238. Kawamura, H. and P. Wu (1998): Formation mechanism of Japan Sea Proper Water in the flux center off Vladivostok. J. Geophys. Res., 103, 21611 21622. Kim, C.-H. and J. H. Yoon (1996): Modeling of the wind-driven circulation in the Japan Sea using a reduced gravity model. J. Oceanogr., 52, 359 373. Kim, M. K. and I. S. Kang (1995): Diagnostic modeling of wind stress, sensible, and latent heat flux on the sea surface around the Korean peninsula. J. Korea. Meteor. Soc., 31, 1 13. Kim, Y.-S. (1992): Estimate of heat transport across the sea surface near Japan with bulk methods. Doctoral Thesis, Univ. of Tokyo, 124 pp. Kondo, J. (1975): Air-sea bulk transfer coefficients in adiabatic conditions. Boundary-Layer Meteor., 9, 91 112. Kurasawa, Y., K. Hanawa and Y. Toba (1983): Heat balance of the surface layer of the sea at Ocean Weather Station T. J. Oceanogr. Soc. Japan, 39, 192 202. Leonov, A. K. (ed.) (1961): Basic Features of the Japan Sea Geology and Hydrology. P.P. Shirshov Inst. of Oceanogr., Moscow (in Russian). Maizuru Marine Observatory (MMO) (1972): Marine meteorological study of the Japan Sea. Tech. Rep. of the Japan Meteor. Agency, 80, 116 pp. (in Japanese). Miyazaki, M. (1952): The heat budget in the Japan Sea. Bull Hokkaido Reg. Fish. Res. Lab., 49, 1 54. Na, J. Y. and J. W. Seo (1997): Upper layer circulation driven by the sea surface wind and heat flux in the East/Japan Sea. Proc. 9th Pams & JECSS, Taiwan, 87 89. Na, J. Y., J. W. Seo and S. K. Han (1992): Monthly-mean sea surface winds over the adjacent seas of the Korea peninsula. J. Oceanol. Soc. Korea, 27, 1 10. Na, J. Y., S. K. Han, J. W. Seo, Y. G. Noh and I. S. Kang (1997): Empirical orthogonal function analysis of surface pressure, sea surface temperature and winds over the East Sea of the Korea (Japan Sea). J. Korean Fish. Soc., 30, 188 202. Park, W. S., I. S. Oh and T. B. Shim (1995): Temporal and spatial distributions of heat fluxes in the East Sea (Sea of Japan). J. Oceanol. Soc. Korea, 30, 91 115. Sakurai, M. A., A. Maeda and T. Yamasiro (1989): The heat and water budget over the East China and the Yellow Seas. Kaiyo Monthly, Symposium, 21, 412 415. Seckel, G. R. and F. H. Beaudry (1973): The radiation from sun and sky over the North Pacific Ocean (abstract). Trans. Amer. Geophys. Union, 54, 1114. Seung, Y. H. and J. H. Yoon (1995): Robust diagnostic modeling of the Japan Sea circulation. J. Oceanogr., 51, 421 440. Shim, T. B. and K. Kim (1981): On the variation of the mixed layer depth and the heat flux in the Sea of Japan. J. Oceanol. Soc. Korea, 16, 49 56. Stanev, E. V. (1994): Assimilation of sea surface temperature data in a numerical ocean circulation model. A study of the water mass formation. p. 33 57. In Data Assimilation: Tools for Modelling the Ocean in a Global Change Perspective, ed. by P. P. Brasseur and J. C. J. Nihoul, NATO ASI Series, 19. 270 J. Na et al.