Simulated Mixed Layer Depth Research Articles

Trends in the ocean mixed‐layer depth in the western North Pacific tropical cyclone basin

AbstractThe upper ocean mixed‐layer depth (MLD) has been recognized as a crucial factor in understanding the impact of climate change on tropical cyclone (TC) intensity, while the specific MLD variations in the western North Pacific (WNP) basin have received comparatively little attention. Using two ocean reanalysis datasets and the output of 28 CMIP6 models, the climatological mean MLD and its trend in the TC active region are examined. Compared to the ORAS4 and EN4 datasets, the spatial pattern of the climatological mean MLD can be well simulated in the multi‐model ensemble (MME). The mean MLD decreases with increasing latitude and maintains the maximum in the equatorial region. The spatial patterns of MLD long‐term (1958–2017) and short‐term (1979–2017) trends are deepening in the TC active region, with the relatively large positive trends occurring to the southeastern WNP primarily between 5°N and 15°N. However, the simulated trend in the MME is dominant with shoaling MLD, and the shoaling of the MLD is also projected under the SSP5‐8.5 scenario. It is suggested that the bias on the simulated shoaling of the MLD in CMIP6 models may result from the overestimated enhancement of the upper‐ocean stratification. Thus, there is a discrepancy between the observed and simulated MLD trends in the WNP basin, which may have implications for TC intensity change under global warming scenarios.

On an Improved Second‐Moment Closure Model for Langmuir Turbulence Conditions and Its Application

AbstractRecently, a k‐ω second‐moment closure (SMC) model including the Langmuir turbulence effects was proposed by Yu et al. (2018, https://doi.org/10.1029/2018jc013878), however, the equations for determining the stability functions in it are very complicated. In this study, the equations of the stability functions are derived in more detail and a new explicit version is proposed. In the meantime, a new constant cω4 = 0.15 is introduced into the turbulent frequency transport equation to manifest the role of the shear generating term caused by the Stokes drift. And then the performance of the new SMC model is investigated by one‐dimensional Papa Ocean Station simulation and three‐dimensional global climate model simulation. The results show that the use of the new SMC model produces significant changes in the results of the ocean surface boundary layer simulations at the Papa Ocean Station, especially for the summer and autumn sea surface temperature (SST) simulations, and for the mixed layer depth (MLD) and mixed layer temperature (MLT) in the mixed layer deepening process. In the three‐dimensional simulation, the new SMC model resulted in a decrease of more than 34% in the annual root mean square error of SST in the northern extratropical region compared to the non‐LT effects model. The simulated MLD for tropical regions in winter and summer has also improved by 61.9% and 53.6%, respectively. The effect of the new SMC model on the MLT is mainly found in the regions beyond the tropical in summer and the tropical and northern extratropical regions in winter.

A numerical study on the mixed layer depth variability and its influence on the sea surface temperature during 2013–2014 in the Bay of Bengal and Equatorial Indian Ocean

This study addresses the air–sea interaction processes and mixed layer variability, which cause the intraseasonal oscillations in the sea surface temperature (SST) during January 2013–December 2014 using the Regional Ocean Modeling System (ROMS). We have analyzed the SST variability at three locations—northern Bay of Bengal (BoB)/15°N, 90°E (R15), central BoB/12°N, 90°E (R12), and equatorial Indian Ocean (EIO)/0°N, 80.5°E (R0). During northeast monsoon (NEM) and southwest monsoon (SWM), intraseasonal SST variability is respectively controlled by the intense outgoing fluxes (sum of longwave radiation, latent heat flux, and sensible heat flux) and zonal wind stress. The intraseasonal SST variability in spring and fall is modulated by intense incoming shortwave radiation. There is a profound impact of mixed layer depth (MLD) variations on the intraseasonal SST oscillations in the BoB and EIO. At R15, and R12, deepened simulated MLD is associated with the lowered SST variability in the NEM and SWM. In spring and fall, the shallow MLD variability corresponds to higher intraseasonal SST variability at the buoy locations. In the northern BoB, ROMS cannot capture barrier layer (BL) and temperature inversion (TI) accurately in the winter and premonsoon season due to salinity bias, resulting in the difference between simulated and actual MLD. But the simulated MLD bias does not affect the intraseasonal SST structures in the NEM and pre-SWM. In the northern BoB, the proper representation of salinity structure may represent BL, TI, and MLD, accurately in the simulation during the winter and premonsoon season.

Modeling of the Influence of Sea Ice Cycle and Langmuir Circulation on the Upper Ocean Mixed Layer Depth and Freshwater Distribution at the West Antarctic Peninsula

AbstractThe Southern Ocean is chronically undersampled due to its remoteness, harsh environment, and sea ice cover. Ocean circulation models yield significant insight into key processes and to some extent obviate the dearth of data; however, they often underestimate surface mixed layer depth (MLD), with consequences for surface water‐column temperature, salinity, and nutrient concentration. In this study, a coupled circulation and sea ice model was implemented for the region adjacent to the West Antarctic Peninsula, a climatically sensitive region which has exhibited decadal trends towards higher ocean temperature, shorter sea ice season, and increasing glacial freshwater input, overlain by strong interannual variability. Hindcast simulations were conducted with different air‐ice drag coefficients and Langmuir circulation parameterizations to determine the impact of these factors on MLD. Including Langmuir circulation deepened the surface mixed layer, with the deepening being more pronounced in the shelf and slope regions. Optimal selection of an air‐ice drag coefficient also increased modeled MLD by similar amounts and had a larger impact in improving the reliability of the simulated MLD interannual variability. This study highlights the importance of sea ice volume and redistribution to correctly reproduce the physics of the underlying ocean, and the potential of appropriately parameterizing Langmuir circulation to help correct for biases towards shallow MLD in the Southern Ocean. The model also reproduces observed freshwater patterns in the West Antarctic Peninsula during late summer and suggests that areas of intense summertime sea ice melt can still show net annual freezing due to high sea ice formation during the winter.

Satellite remote-sensing observations for definitions of areas for marine conservation: Case study of the Scotian Slope, Eastern Canada

Characterizing offshore areas for marine conservation faces impediment from logistics and costs of in situ data collection. This study leveraged the high spatial and temporal coverage provided by remote-sensing ocean colour products, and the concept of biogeographical classification to delineate areas in the pelagic environment with application to marine conservation. Satellite-derived and modelled biogeophysical data were used to delineate an area of biological and physical homogeneity spatially consistent with the static boundaries of the Scotian Slope Ecologically and Biologically Significant Area (EBSA), off eastern Canada. We used iterative cluster analysis applied to an archive (2004–2014) that consisted of remotely-sensed Chlorophyll a, sea-surface temperature, and primary production derived from the Moderate resolution Imaging Spectroradiometer (MODIS), and simulated mixed layer depth to define “dynamic” boundaries of the EBSA at bi-weekly, seasonal and annual resolutions. The final cluster extended further east than the static EBSA in summer and fall, indicating that characteristics of the static EBSA environment persist beyond the current boundaries in these seasons. In winter and spring, the final areas derived by our analysis was smaller than the static EBSA, but again showed extension beyond the current eastern boundary. Both ice and cloud cover affecting remotely-sensed data and the extent of water column mixing were important in determining the size of the final cluster. The dynamic cluster east of the original static boundary incorporated an area of lower Chlorophyll a and water column primary production in the spring, but higher values in the autumn relative to the static area. Overall physical and biological characteristics of the static and dynamic EBSA considered in this research were similar within and across years. This methodology incorporates ocean-colour data and modelled estimates of multiple biological and physical characteristics to objectively refine areas of ecological interest at a spatial scale relevant for the management of marine conservation areas.

Assessing the Effects of Langmuir Turbulence on the Entrainment Buoyancy Flux in the Ocean Surface Boundary Layer

AbstractLarge-eddy simulations (LESs) with various constant wind, wave, and surface destabilizing surface buoyancy flux forcing are conducted, with a focus on assessing the impact of Langmuir turbulence on the entrainment buoyancy flux at the base of the ocean surface boundary layer. An estimate of the entrainment buoyancy flux scaling is made to best fit the LES results. The presence of Stokes drift forcing and the resulting Langmuir turbulence enhances the entrainment rate significantly under weak surface destabilizing buoyancy flux conditions, that is, weakly convective turbulence. In contrast, Langmuir turbulence effects are moderate when convective turbulence is dominant and appear to be additive rather than multiplicative to the convection-induced mixing. The parameterized unresolved velocity scale in the K-profile parameterization (KPP) is modified to adhere to the new scaling law of the entrainment buoyancy flux and account for the effects of Langmuir turbulence. This modification is targeted on common situations in a climate model where either Langmuir turbulence or convection is important and may overestimate the entrainment when both are weak. Nevertheless, the modified KPP is tested in a global climate model and generally outperforms those tested in previous studies. Improvements in the simulated mixed layer depth are found, especially in the Southern Ocean in austral summer.

Seasonal variation of the global mixed layer depth: comparison between Argo data and FIO-ESM

The present study evaluates a simulation of the global ocean mixed layer depth (MLD) using the First Institute of Oceanography-Earth System Model (FIOESM). The seasonal variation of the global MLD from the FIO-ESM simulation is compared to Argo observational data. The Argo data show that the global ocean MLD has a strong seasonal variation with a deep MLD in winter and a shallow MLD in summer, while the spring and fall seasons act as transitional periods. Overall, the FIO-ESM simulation accurately captures the seasonal variation in MLD in most areas. It exhibits a better performance during summer and fall than during winter and spring. The simulated MLD in the Southern Hemisphere is much closer to observations than that in the Northern Hemisphere. In general, the simulated MLD over the South Atlantic Ocean matches the observation best among the six areas. Additionally, the model slightly underestimates the MLD in parts of the North Atlantic Ocean, and slightly overestimates the MLD over the other ocean basins.

Statistical models of global Langmuir mixing

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

Reconstructing extreme AMOC events through nudging of the ocean surface: a perfect model approach

While the Atlantic Meridional Overturning Circulation (AMOC) is thought to be a crucial component of the North Atlantic climate, past changes in its strength are challenging to quantify, and only limited information is available. In this study, we use a perfect model approach with the IPSL-CM5A-LR model to assess the performance of several surface nudging techniques in reconstructing the variability of the AMOC. Special attention is given to the reproducibility of an extreme positive AMOC peak from a preindustrial control simulation. Nudging includes standard relaxation techniques towards the sea surface temperature and salinity anomalies of this target control simulation, and/or the prescription of the wind-stress fields. Surface nudging approaches using standard fixed restoring terms succeed in reproducing most of the target AMOC variability, including the timing of the extreme event, but systematically underestimate its amplitude. A detailed analysis of the AMOC variability mechanisms reveals that the underestimation of the extreme AMOC maximum comes from a deficit in the formation of the dense water masses in the main convection region, located south of Iceland in the model. This issue is largely corrected after introducing a novel surface nudging approach, which uses a varying restoring coefficient that is proportional to the simulated mixed layer depth, which, in essence, keeps the restoring time scale constant. This new technique substantially improves water mass transformation in the regions of convection, and in particular, the formation of the densest waters, which are key for the representation of the AMOC extreme. It is therefore a promising strategy that may help to better constrain the AMOC variability and other ocean features in the models. As this restoring technique only uses surface data, for which better and longer observations are available, it opens up opportunities for improved reconstructions of the AMOC over the last few decades.

Joint assimilation of Aquarius‐derived sea surface salinity and AVHRR‐derived sea surface temperature in an ocean general circulation model using SEEK filter: Implication for mixed layer depth and barrier layer thickness

AbstractSea surface salinity (SSS) from Aquarius mission and sea surface temperature (SST) from Advanced Very High Resolution Radiometer (AVHRR) for the years 2012–2014 are assimilated into the global Massachusetts Institute of Technology General Circulation Model (MITGCM). Investigation of the impact of assimilation of these two data sets on simulated mixed layer depth (MLD) and barrier layer thickness (BLT) forms the core of our study. The method of assimilation is the Singular Evolutive Extended Kalman (SEEK) filter. Several assimilation runs are performed. Single‐parameter assimilation, as well as joint assimilation, is conducted. To begin with, the model simulated SST and SSS are compared with independent Argo observations of these two parameters. Use of latitudinally varying error variances, which is a novel feature of our study, gives rise to the significant improvement in the simulation of SSS and SST. The best result occurs when joint assimilation is performed. Afterward, simulated MLD and BLT are compared with the same parameters derived from Argo observations forming an independent validation data set. Comparisons are performed both in temporal and spatial domains. Significant positive impact of assimilation is found in all the cases studied, and joint assimilation is found to outperform single‐parameter assimilation in each of the cases considered. It is found that simulations of MLD and BLT improve up to 24% and 29%, respectively, when a joint assimilation of SSS and SST is carried out.

An EnOI Assimilation of Satellite Data in an Indian Ocean Circulation Model

Ensemble optimal interpolation, a simplified and computationally inexpensive version of ensemble Kalman filter, has been used to assimilate satellite-derived sea level anomaly and sea surface temperature in an Indian Ocean circulation model. In order to cut off the long-range spurious covariances, a localization technique has also been used where an assumption is made that only measurements located within a certain influence radius of a grid point can affect the analysis at that grid point. It has been found that the analyses fit the assimilated observations quite well. For a more stringent test of the power of the assimilation technique, selected regions have been demarcated in the analysis area. Simulated mixed layer depth, depth of the 20 °C isotherm, and temperature at 400-m depth have been compared with observations of these variables in these regions, and assimilation has been found to exhibit significant positive impact. Simulated surface and subsurface temperatures have been compared at isolated Research moored array for African-Asian-Australian monsoon analysis and prediction (RAMA) buoy locations, and again, the high positive impact of assimilation has been evident from these comparisons. Finally, the impact of assimilation on surface current simulation at selected RAMA buoy locations has been found to be somewhat marginal, and a significant improvement apparently needs additional assimilation of drifter data with a very high concentration of drifters.

A study of the mixed layer of the South China Sea based on the multiple linear regression

Multiple linear regression (MLR) method was applied to quantify the effects of the net heat flux (NHF), the net freshwater flux (NFF) and the wind stress on the mixed layer depth (MLD) of the South China Sea (SCS) based on the simple ocean data assimilation (SODA) dataset. The spatio-temporal distributions of the MLD, the buoyancy flux (combining the NHF and the NFF) and the wind stress of the SCS were presented. Then using an oceanic vertical mixing model, the MLD after a certain time under the same initial conditions but various pairs of boundary conditions (the three factors) was simulated. Applying the MLR method to the results, regression equations which modeling the relationship between the simulated MLD and the three factors were calculated. The equations indicate that when the NHF was negative, it was the primary driver of the mixed layer deepening; and when the NHF was positive, the wind stress played a more important role than that of the NHF while the NFF had the least effect. When the NHF was positive, the relative quantitative effects of the wind stress, the NHF, and the NFF were about 10, 6 and 2. The above conclusions were applied to explaining the spatio-temporal distributions of the MLD in the SCS and thus proved to be valid.

The Role Of Surface Waves On The Upper Ocean: Application In Indonesian Seas

Surface waves are the most energetic processes in the oceans, due to their strong effects on the exchanges of momentum, heat, and mass through the air-sea interface. The effects of surface waves now are applied to the development of an ocean forecast system around Indonesian Seas by employing the MASNUM wave-circulation coupled numerical model. The model was set up for the area of 300 – 1500 E, 200 S – 500 N. The numerical model covers the Indian Ocean, Indonesian Seas, South China Sea (SCS), and western Pacific. The preliminary results show that the significant wave height in southern part of Indonesia is mostly influenced by the wave in Indian Ocean, while in the northwest of Indonesia, it is much affected by the wave in SCS. In Indonesia Seas, the value of Bv is less than 500 cm2/s and the depth of penetration could reach 25 m. By including the wave- induced mixing into the circulation model, the simulation of the upper ocean temperature is improved, and the simulated mixed layer depth is 10 – 15 m deeper which is closer to observation. During the upwelling favorable season, the distribution of ML depth along west coast of Sumatra to south Java is 10 m deeper by adding Bv.

Simulation of Mixed Layer Depth in the Northeast Pacific Utilizing Spectral Nudging

Abstract A numerical model, the Parallel Ocean Program (POP), is used to run a 46-yr simulation of the North Pacific Ocean beginning in January 1960. The model has 0.25° horizontal resolution and 28 vertical levels, and it employs spectral nudging, which, unlike standard nudging, nudges only specific frequency and wavenumber bands. This simulation is nudged to the mean and annual Levitus climatological potential temperature and salinity. The model was forced with National Centers for Environmental Prediction (NCEP) mean monthly winds, sea level pressure, net heat flux, and rain rate. The simulated mixed layer depths (MLD) suggest significant shoaling of the MLD between 1970 and 2006, with faster rates in the northern Gulf of Alaska and slower rates to the west and south of Line Papa. The rates are of similar magnitude to those found in past studies and are consistent with the observed freshening and warming of the upper waters in the Gulf of Alaska. The rates are not spatially uniform, and the simulated MLD in the northeast Pacific actually deepens with time at some locations. These regions of increase form zonal bands in the simulation. The simulated MLD at Ocean Weather Station Papa (OWSP) shoals on average, but it is located close to one of these deepening bands. On average, the simulated, low-frequency MLD at OWSP gives a good indication of the MLD along Line Papa and in the Gulf of Alaska near Line Papa’s latitude. The correlation coefficient between the MLD at OWSP and the latitudinal average of the MLD within the greater Gulf of Alaska (with OWSP removed) is 0.7 at zero lag. The correlation coefficient between the MLD at OWSP and the latitudinal average along Line Papa alone (with OWSP removed) is 0.6 at zero lag. Observed variability of the MLD along Line Papa and at OWSP is reproduced by the model. However, there is considerable spatial variability in the simulated MLD in the Gulf of Alaska as a whole, so MLD variability at OWSP is not necessarily a good indicator of the MLD variability throughout the region. Over the span of the simulation, the low-frequency MLD variability in the Gulf of Alaska is better correlated to the North Pacific Gyre Oscillation (NPGO) than to either the Pacific decadal oscillation (PDO) or Southern Oscillation index (SOI).

Effect of River Discharge on Bay of Bengal Circulation

The seasonal circulation and mixed layer depths in Bay of Bengal is modeled using the three-dimensional Princeton Ocean Model (POM). Along the coastal boundaries a higher resolution is accomplished using the curvilinear orthogonal grid. Model uses a free-surface and terrain following sigma coordinates. The initial climatological salinity and temperature fields for the model are derived from the World Ocean Atlas-2001(WOA01). The Model is forced with wind stress derived from COADS wind climatology. Bilinear interpolation is used to obtain the initial fields and wind stress to the required model specification. Using the seasonal fields and wind stress the model is integrated for simulating Bay of Bengal circulation. The numerical simulations on climatological scale for monsoon months were conducted to study the evolution of dynamics. The simulations bring out not only the typical characteristic features of fresh water plume along the coast but also intensification of the flow over the monsoon period. The increase in the fresh water flow found to affect only the western parts of the BoB. The opposing currents due to monsoon winds and southward flowing fresh water discharge (FWD) were also delineated. The model results show that the wind stress induced turbulence process is subdued in the presence of strong vertical salinity stratification due to the influence of FWD. The simulated mixed layer depths are in agreement with the reported analytical energy required for mixing values.

An improvement of the too cold tongue in the tropical Pacific with the development of an ocean-wave-atmosphere coupled numerical model

A common problem in the application of the coupled ocean-atmosphere general circulation models (CGCMs) without flux correction is that the simulated equatorial cold tongue in general tends to be too strong, narrow, and extending too far west. The causes are not well understood yet. One possible reason may be the simulated mixed layer depth (MLD) is too shallow in the tropical Pacific due to insufficient vertical mixing in the OGCM. It is believed that the wave-induced vertical mixing can greatly improve the simulation of the MLD and thermocline structure. In this study, the coupled ocean-atmosphere general circulation model (FGCM-0) incorporated with wave-induced mixing has been employed to simulate the tropical Pacific sea surface temperature (SST). Generally, the wave-induced mixing lowers the SST in the OGCM because the strengthened vertical mixing can bring more cold water upward. However, in the coupled model, the non-uniformity of the space distribution in SST drop generates a horizontal gradient of...

Ocean mixed layer depth: A subsurface proxy of ocean‐atmosphere variability

A new criterion, based on the shallowest extreme curvature of near surface layer density or temperature profiles, is established for demarking the mixed layer depth, hmix. Using historical global hydrographic profile data, including conductivity‐temperature‐depth and expendable bathythermograph data obtained during World Ocean Circulation Experiment, its seasonal variability and monthly to interannual anomalies are computed. Unlike the more commonly used Δ criterion, the new criterion is able to deal with both different vertical resolutions of the data set and a large variety of observed stratification profiles. For about two thirds of the profiles our algorithm produces an hmix/c that is more reliable than the one of the Δ criterion. The uncertainty for hmix/c is ±5 m for high‐ (<5 m) and ±8 m for low‐ (<20 m) resolution profiles. A quality index, QImix, which compares the variance of a profile above hmix to the variance to a depth of 1.5 × hmix, shows that for the 70% of the profile data for which a clearly recognizable well‐mixed zone exists near the surface, our criterion identifies the depth of the well‐mixed zone in all cases. The standard deviation of anomalous monthly hmix/c is typically 20–70% of the long‐term mean hmix/c. In the tropical Pacific the monthly mean anomalies of hmix/c are not well correlated with anomalies of sea surface temperature, which indicate that a variety of turbulent processes, other than surface heat fluxes, are important in the upper ocean there. Comparisons between observed hmix/c and Massachusetts Institute of Techonology/ocean general circulation model/Estimating the Circulation and Climate of the Ocean model simulated mixed layer depth indicate that the KPP algorithm captures in general a 30% smaller mixed layer depth than observed.

Air-sea Coupling During the Tropical Cyclones in the Indian Ocean: A Case Study Using Satellite Observations

In the years 1999 and 2001, three intense tropical cyclones formed over the northern Indian Ocean—two over the Bay of Bengal during 15–19 and 25–29 October, 1999 and one over the Arabian Sea during 21–28 May, 2001. We examined the thermal, salinity and circulation responses at the sea surface due to these severe cyclones in order to understand the air-sea coupling using data from satellite measurements and model simulations. It is found that the Sea Surface Temperature (SST) cooled by about 0.5 °–0.8 °C in the Bay of Bengal and 2 °C in the Arabian Sea. In the Bay of Bengal, this cooling took place beneath the cyclone center whereas in the Arabian Sea, the cooling occurred behind the cyclone only a few days later. This contrasting oceanic response resulted mainly from the salinity stratification in the Bay of Bengal and thermal stratification in the Arabian Sea and the associated mixing processes. In particular, the cyclones moved over the region of low salinity and smaller mixed layer depth with a distinct mixed layer deepening to the left side of the cyclone track. It is envisaged that daily satellite estimates of SST and Sea Surface Salinity (SSS) using Outgoing Longwave Radiation (OLR) and model simulated mixed layer depth would be useful for the study of tropical cyclones and prediction of their path over the northern Indian Ocean.

Effects of high‐frequency wind sampling on simulated mixed layer depth and upper ocean temperature

Effects of high‐frequency wind sampling on a near‐global ocean model are studied by forcing the model with a 12 hourly averaged wind product and its 24 hourly subsamples in separate experiments. The differences in mixed layer depth and sea surface temperature resulting from these experiments are examined, and the underlying physical processes are investigated. The 24 hourly subsampling not only reduces the high‐frequency variability of the wind but also affects the annual mean wind because of aliasing. While the former effect largely impacts mid‐ to high‐latitude oceans, the latter primarily affects tropical and coastal oceans. At mid‐ to high‐latitude regions the subsampled wind results in a shallower mixed layer and higher sea surface temperature because of reduced vertical mixing associated with weaker high‐frequency wind. In tropical and coastal regions, however, the change in upper ocean structure due to the wind subsampling is primarily caused by the difference in advection resulting from aliased annual mean wind, which varies with the subsampling time. The results of the study indicate a need for more frequent sampling of satellite wind measurement and have implications for data assimilation in terms of identifying the nature of model errors.

Seasonal variability of thermocline in the Yellow Sea

Based on the MASNUM wave-tide-circulation coupled numerical model, seasonal variability of thermocline in the Yellow Sea was simulated and compared with in-situ observations. Both simulated mixed layer depth (MLD) and thermocline intensity have similar spatial patterns to the observations. The simulated maximum MLD are 8 m and 22 m, while the corresponding observed values are 13 m and 27 m in July and October, respectively. The simulated thermocline intensity are 1.2°C/m and 0.5°C/m in July and October, respectively, which are 0.6°C/m less than those of the observations. It may be the main reason why the simulated thermocline is weaker than the observations that the model vertical resolution is less precise than that of the CTD data which is 1 m. Contours of both simulated and observed thermocline intensity present a circle in general. The wave-induced mixing plays a key role in the formation of the upper mixed layer in spring and summer. Tidal mixing enhances the thermocline intensity. Buoyancy-driven mixing destroys the thermocline in autumn and keeps the vertical temperature uniform in winter.