Simulation and exploration of the mechanisms underlying the spatiotemporal distribution of surface mixed layer depth in a large shallow lake

2012 ◽  
Vol 29 (6) ◽  
pp. 1360-1373 ◽  
Author(s):  
Qiaohua Zhao ◽  
Jihua Sun ◽  
Guangwei Zhu
Keyword(s):  
Mixed Layer ◽  
Shallow Lake ◽  
Mixed Layer Depth ◽  
Spatiotemporal Distribution ◽  
Surface Mixed Layer ◽  
Layer Depth ◽  
Large Shallow Lake

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.

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 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.

Effect of climate warming on the mixed layer depth in lakes

2020 ◽  
Author(s):  
Tom Shatwell ◽  
Georgiy Kirillin
Keyword(s):  
Mixed Layer ◽  
Climate Warming ◽  
Climate Models ◽  
Global Climate ◽  
Mixed Layer Depth ◽  
Global Radiation ◽  
Global Climate Models ◽  
Surface Mixed Layer ◽  
Layer Depth ◽  
Modelling Studies

<p>The surface mixed layer in lakes is where phytoplankton grow and where most of the primary production occurs. Knowledge of the thickness of the mixed layer is essential to estimate for instance primary productivity and to interpret remote sensing measurements, because it determines the mean light supply and indicates how homogeneous the water column is. Modelling studies, primarily in the ocean, have concluded that the mixed layer will shoal as a result of climate warming, but the empirical evidence does not support this. Here we seek to determine how climate change affects the mixed layer thickness and mean underwater irradiance in lakes. We use an ensemble modelling approach to simulate mixed layer depth in 3 warming scenarios (RCP2.6, 6.0, 8.5) in about 50 lakes across the globe using the hydrodynamic model Flake forced by four downscaled global climate models. Results indicate that warming has little direct effect on the mixed layer depth. Mean underwater light in the mixed layer was nevertheless projected to increase as a result of the global radiation increases in the global climate models.</p>

scholarly journals Mesoscale and Submesoscale Effects on Mixed Layer Depth in the Southern Ocean

2017 ◽  
Vol 47 (9) ◽  
pp. 2173-2188 ◽  
Author(s):  
S. D. Bachman ◽  
J. R. Taylor ◽  
K. A. Adams ◽  
P. J. Hosegood
Keyword(s):  
Southern Ocean ◽  
Mixed Layer ◽  
Large Scale ◽  
Mixed Layer Depth ◽  
Surface Mixed Layer ◽  
Grid Spacing ◽  
Layer Depth ◽  
State Estimate ◽  
Nested Models ◽  
Significant Difference

AbstractSubmesoscale dynamics play a key role in setting the stratification of the ocean surface mixed layer and mediating air–sea exchange, making them especially relevant to anthropogenic carbon uptake and primary productivity in the Southern Ocean. In this paper, a series of offline-nested numerical simulations is used to study submesoscale flow in the Drake Passage and Scotia Sea regions of the Southern Ocean. These simulations are initialized from an ocean state estimate for late April 2015, with the intent to simulate features observed during the Surface Mixed Layer at Submesoscales (SMILES) research cruise, which occurred at that time and location. The nested models are downscaled from the original state estimate resolution of 1/12° and grid spacing of about 8 km, culminating in a submesoscale-resolving model with a resolution of 1/192° and grid spacing of about 500 m. The submesoscale eddy field is found to be highly spatially variable, with pronounced hot spots of submesoscale activity. These areas of high submesoscale activity correspond to a significant difference in the 30-day average mixed layer depth between the 1/12° and 1/192° simulations. Regions of large vertical velocities in the mixed layer correspond with high mesoscale strain rather than large . It is found that is well correlated with the mesoscale density gradient but weakly correlated with both the mesoscale kinetic energy and strain. This has implications for the development of submesoscale eddy parameterizations that are sensitive to the character of the large-scale flow.

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

scholarly journals Organic nutrients as sources of N and P to the upper layers of the North Atlantic subtropical gyre along 24.5° N

2010 ◽  
Vol 7 (3) ◽  
pp. 4001-4044
Author(s):  
A. Landolfi ◽  
H. Dietze ◽  
W. Koeve ◽  
R. Mather ◽  
R. Sanders
Keyword(s):  
Mixed Layer ◽  
North Atlantic ◽  
N2 Fixation ◽  
Mixed Layer Depth ◽  
Subtropical Gyre ◽  
Surface Mixed Layer ◽  
Layer Depth ◽  
The North ◽  
Nutrient Utilisation ◽  
The North Atlantic

Abstract. There is a longstanding discussion on how the macronutrient requirement of the export production in the North Atlantic subtropical gyre is sustained. In this study we asses the role of dissolved organic nitrogen (DON) and phosphorous (DOP) as sources of new nutrients into the North Atlantic subtropical gyre at 24.5° N. We define, based on measurements of DON, DOP, phytoplankton community structure, stable nitrogen isotopic signals, surface mixed layer depth and ocean color as viewed from space, four regions characterized by different nutrient supply regimes. Within these regions, two distinct loci of N2 fixation occur associated with different plankton assemblages and separated by a region in which N2 fixation occurs at levels insufficient to leave its distinctive isotopic fingerprint on the isotopic composition of PON. Here, the phosphorus supply pathways to the mixed plankton assemblage appear to be different. In the wester oligotrophic gyre (70–46° W), the lateral advection of DOP supplies the missing P that, together with, shallow mixed layer, almost permanent stratification and high water temperatures, stimulate diazotrophic growth, which augment TON local accumulation. In the eastern oligotophic gyre (46–30° W), DOP cannot support the P demand as it is exhausted on its way from productive areas. This is inferred from DOP turnover rates, estimated form enzymatic clevage rates, which are shorter (11 ± 8 months) than transit timescales, estimated from a 3-D circulation model (>4 yr). A stronger seasonal cycle in chlorophyll and mixed layer depth, favour some nutrient injections from below. Here additional N sources come from the advected DON which has a turnover-time of 6.7 ± 3 yr, instead fast remineralization and little DOP export are needed to maintain the P requirements. We conclude from these observations that organic nutrient utilisation patterns drive diverse phytoplankton assemblages and oceanic nitrogen fixation gradients.

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