Comparison of the Observed Mixed Layer Depth in the Lee of the Hawaiian Island to the Modeled Mixed Layer Depth of the Regional Navy Coastal Ocean Model

2013 ◽  
Vol 47 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Jeffery Todd Rayburn ◽  
Vladimir M. Kamenkovich
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Sea Surface ◽  
Height Anomaly ◽  
Surface Mixed Layer ◽  
Layer Depth ◽  
Coastal Ocean Model

AbstractThis study evaluates the ability of the Hawaii Regional Navy Coastal Ocean Model to accurately predict the depth of the surface mixed layer in the lee of the Hawaiian Islands. Accurately modeling the depth of the surface mixed layer in this complex wake island environment is important to naval operations because the area hosts numerous training exercises. The simulated data were compared to CTD data collected from sea gliders, and tests for correlation were conducted. For mixed layer depths that did show correlation, match-paired t tests were used to determine the significance of the correlations. It was determined that the Hawaii Regional Navy Coastal Ocean Model has difficulty accurately predicting the depth of the surface mixed layer. It was also determined that the model has difficulty with unusual oceanographic features such as mode water eddies. These features are too uncommon and short-lived to be depicted in the climatology data. The climatology data are a major component of the synthetic profiles that the model generates, and these profiles tend to smooth out the unusual subsurface isothermal layer.List of AbbreviationsBT ‐ bathythermographsCCE ‐ cold core eddyCOAMPS ‐ Coupled Ocean/Atmosphere Mesoscale Prediction SystemCTD ‐ conductivity, temperature, and depthGDEM ‐ Generalized Digital Environmental ModelIR ‐ infraredMLD ‐ mixed layer depthMODAS ‐ Modular Ocean Data Assimilation SystemMOODS ‐ Master Oceanographic Observation DatasetNCODA ‐ Navy Coupled Ocean Data AssimilationNCOM1 ‐ Hawaii Regional Navy Coastal Ocean Model with in situ assimilationNCOM2 ‐ Hawaii Regional Navy Coastal Ocean Model without in situ assimilationPAVE ‐ Profile Analysis and Visualization EnvironmentSSHa ‐ sea surface height anomaly derived from altimetrySST ‐ sea surface temperatureWCE ‐ warm core eddy

Statistical features of the Oceanographic area off south-western Australia, obtained from Bathythermograph data

1986 ◽  
Vol 37 (4) ◽  
pp. 421 ◽  
Author(s):  
LJ Hamilton
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Temperature Fields ◽  
Surface Mixed Layer ◽  
Statistical Features ◽  
Layer Depth ◽  
Leeuwin Current ◽  
South West

A statistical analysis has been made of 26 years of bathythermograph (BT) data to 1980 for the south-west Australian area bounded by 30-35�s. and 110-115�E., a region influenced by the Leeuwin Current. The data indicate that a surface mixed layer exists all year round, with average depth 55 m and standard deviation 37 m. All but 2% of BT casts show a mixed-layer depth (MLD) less than 150 m. MLD are deepest in mid-year, particularly from July to September. Sea surface temperatures (SST) are significantly related to temperature values down to 200 m depth, especially in mid-year, for both eastern and western parts of the area separated by 113�E. Correlations of MLD with SST are significant only in the western part, and then only from January to March, and April to June. Long-term horizontally averaged temperature fields are broadly related through the water column from the surface to 200 m. All results indicate that, especially in mid-year, SST fields are related to subsurface temperature fields, which may be representative of flow structure. Seasonal differences exist between the eastern and western areas, caused by the Leeuwin Current.

scholarly journals Global sensitivity analysis of the Indian monsoon during the Pleistocene

2015 ◽  
Vol 11 (1) ◽  
pp. 45-61 ◽  
Author(s):  
P. A. Araya-Melo ◽  
M. Crucifix ◽  
N. Bounceur
Keyword(s):  
Sensitivity Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Global Sensitivity Analysis ◽  
Indian Monsoon ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Layer Depth ◽  
Global Sensitivity

Abstract. The sensitivity of the Indian monsoon to the full spectrum of climatic conditions experienced during the Pleistocene is estimated using the climate model HadCM3. The methodology follows a global sensitivity analysis based on the emulator approach of Oakley and O'Hagan (2004) implemented following a three-step strategy: (1) development of an experiment plan, designed to efficiently sample a five-dimensional input space spanning Pleistocene astronomical configurations (three parameters), CO2 concentration and a Northern Hemisphere glaciation index; (2) development, calibration and validation of an emulator of HadCM3 in order to estimate the response of the Indian monsoon over the full input space spanned by the experiment design; and (3) estimation and interpreting of sensitivity diagnostics, including sensitivity measures, in order to synthesise the relative importance of input factors on monsoon dynamics, estimate the phase of the monsoon intensity response with respect to that of insolation, and detect potential non-linear phenomena. By focusing on surface temperature, precipitation, mixed-layer depth and sea-surface temperature over the monsoon region during the summer season (June-July-August-September), we show that precession controls the response of four variables: continental temperature in phase with June to July insolation, high glaciation favouring a late-phase response, sea-surface temperature in phase with May insolation, continental precipitation in phase with July insolation, and mixed-layer depth in antiphase with the latter. CO2 variations control temperature variance with an amplitude similar to that of precession. The effect of glaciation is dominated by the albedo forcing, and its effect on precipitation competes with that of precession. Obliquity is a secondary effect, negligible on most variables except sea-surface temperature. It is also shown that orography forcing reduces the glacial cooling, and even has a positive effect on precipitation. As regards the general methodology, it is shown that the emulator provides a powerful approach, not only to express model sensitivity but also to estimate internal variability and detect anomalous simulations.

scholarly journals Observations of the Transition Layer

2009 ◽  
Vol 39 (3) ◽  
pp. 780-797 ◽  
Author(s):  
T. M. Shaun Johnston ◽  
Daniel L. Rudnick
Keyword(s):  
Layer Thickness ◽  
Mixed Layer ◽  
Potential Vorticity ◽  
Transition Layer ◽  
Mixed Layer Depth ◽  
Density Ratio ◽  
Horizontal Resolution ◽  
Surface Mixed Layer ◽  
Layer Depth ◽  
Vertical Displacements

Abstract The transition layer is the poorly understood interface between the stratified, weakly turbulent interior and the strongly turbulent surface mixed layer. The transition layer displays elevated thermohaline variance compared to the interior and maxima in current shear, vertical stratification, and potential vorticity. A database of 91 916 km or 25 426 vertical profiles of temperature and salinity from SeaSoar, a towed vehicle, is used to define the transition layer thickness. Acoustic Doppler current measurements are also used, when available. Statistics of the transition layer thickness are compared for 232 straight SeaSoar sections, which range in length from 65 to 1129 km with typical horizontal resolution of ∼4 km and vertical resolution of 8 m. Transition layer thicknesses are calculated in three groups from 1) vertical displacements of the mixed layer base and of interior isopycnals into the mixed layer; 2) the depths below the mixed layer depth of peaks in shear, stratification, and potential vorticity and their widths; and 3) the depths below or above the mixed layer depth of extrema in thermohaline variance, density ratio, and isopycnal slope. From each SeaSoar section, the authors compile either a single value or a median value for each of the above measures. Each definition yields a median transition layer thickness from 8 to 24 m below the mixed layer depth. The only exception is the median depth of the maximum isopycnal slope, which is 37 m above the mixed layer base, but its mode is 15–25 m above the mixed layer base. Although the depths of the stratification, shear, and potential vorticity peaks below the mixed layer are not correlated with the mixed layer depth, the widths of the shear and potential vorticity peaks are. Transition layer thicknesses from displacements and the full width at half maximum of the shear and potential vorticity peak give transition layer thicknesses from 0.11× to 0.22× the mean depth of the mixed layer. From individual profiles, the depth of the shear peak below the stratification peak has a median value of 6 m, which shows that momentum fluxes penetrate farther than buoyancy fluxes. A typical horizontal scale of 5–10 km for the transition layer comes from the product of the isopycnal slope and a transition layer thickness suggesting the importance of submesoscale processes in forming the transition layer. Two possible parameterizations for transition layer thickness are 1) a constant of 11–24 m below the mixed layer depth as found for the shear, stratification, potential vorticity, and thermohaline variance maxima and the density ratio extrema; and 2) a linear function of mixed layer depth as found for isopycnal displacements and the widths of the shear and potential vorticity peaks.

scholarly journals Eastern Tropical Atlantic Mixed Layer Depth: Assessment of Methods from In Situ Profiles in the Gulf of Guinea from Coastal to High Sea

2019 ◽  
Vol 36 (1) ◽  
pp. 201-212
Author(s):  
Benjamin Kouadio N’Guessan ◽  
Aka Marcel Kouassi ◽  
Albert Trokourey ◽  
Elisée Toualy ◽  
Desiré Kouamé Kanga ◽  
...  
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Atlantic ◽  
Gulf Of Guinea ◽  
Layer Depth

scholarly journals Scaling Surface Mixing/Mixed Layer Depth under Stabilizing Buoyancy Flux

2015 ◽  
Vol 45 (1) ◽  
pp. 247-258 ◽  
Author(s):  
Yutaka Yoshikawa
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Mixing Layer ◽  
Buoyancy Flux ◽  
Earth’S Rotation ◽  
Surface Mixed Layer ◽  
Threshold Method ◽  
Layer Depth ◽  
Earth's Rotation ◽  
Surface Buoyancy

AbstractThis study concerns the combined effects of Earth’s rotation and stabilizing surface buoyancy flux upon the wind-induced turbulent mixing in the surface layer. Two different length scales, the Garwood scale and Zilitinkevich scale, have been proposed for the stabilized mixing layer depth under Earth’s rotation. Here, this study analyzes observed mixed layer depth plus surface momentum and buoyancy fluxes obtained from Argo floats and satellites, finding that the Zilitinkevich scale is more suited for observed mixed layer depths than the Garwood scale. Large-eddy simulations (LESs) reproduce this observed feature, except under a weak stabilizing flux where the mixed layer depth could not be identified with the buoyancy threshold method (because of insufficient buoyancy difference across the mixed layer base). LESs, however, show that the mixed layer depth if defined with buoyancy ratio relative to its surface value follows the Zilitinkevich scale even under such a weak stabilizing flux. LESs also show that the mixing layer depth is in good agreement with the Zilitinkevich scale. These findings will contribute to better understanding of the response of stabilized mixing/mixed layer depth to surface forcings and hence better estimation/prediction of several processes related to stabilized mixing/mixed layer depth such as air–sea interaction, subduction of surface mixed layer water, and spring blooming of phytoplankton biomass.

scholarly journals Interannual Variability of the Wind-Wave Regime Parameters in the Black Sea

2020 ◽  
Vol 27 (5) ◽  
Author(s):  
P. N. Lishaev ◽  
V. V. Knysh ◽  
G. K. Korotaev ◽  
◽  
◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Black Sea ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Temperature Fields ◽  
The Black Sea ◽  
Layer Depth ◽  
Upper Mixed Layer

Purpose. The investigation is aimed at increasing accuracy of the temperature field reconstruction in the Black Sea upper layer. For this purpose, satellite observations of the sea surface temperature and the three-dimensional fields of temperature (in the 50–500 m layer) and salinity (in the 2.5–500 m layer) pseudo-measurements, previously calculated by the altimetry and the Argo floats data, were jointly assimilated in the Marine Hydrophysical Institute model. Methods and Results. Assimilation of the sea surface temperature satellite observations is the most effective instrument in case the discrepancies between the sea surface and the model temperatures are extrapolated over the upper mixed layer depth up to its lower boundary. Having been analyzed, the temperature profiles resulted from the forecast calculation for 2012 and from the Argo float measurements made it possible to obtain a simple criterion (bound to the model grid) for determining the upper mixed layer depth, namely the horizon on which the temperature gradient was less or equal to ≤ 0.017 °C/m. Within the upper mixed layer depth, the nudging procedure of satellite temperature measurements with the selected relaxation factor and the measurement errors taken into account was used in the heat transfer equation. The temperature and salinity pseudo-measurements were assimilated in the model by the previously proposed adaptive statistics method. To test the results of the sea surface temperature assimilation, the Black Sea hydrophysical fields were reanalyzed for 2012. The winter-spring period (January – April, December) is characterized by the high upper mixed layer depths, well reproducible by the Pacanowski – Philander parameterization, and also by the low values (as compared to the measured ones) of the basin-averaged monthly mean square deviations of the simulated temperature fields. The increased mean square deviations in July – September are explained by absence of the upper mixed layer in the temperature profiles measured by the Argo floats that is not reproduced by the Pacanowski – Philander parameterization. Conclusions. The algorithm for assimilating the sea surface temperature together with the profiles of the temperature and salinity pseudo-measurements reconstructed from the altimetry data was realized. Application of the upper mixed layer depths estimated by the temperature vertical profiles made it possible to correct effectively the model temperature by the satellite-derived sea surface temperature, especially for a winter-spring period. It permitted to reconstruct the temperature fields in the sea upper layer for 2012 with acceptable accuracy.

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