scholarly journals Influence of Pycnocline Smoothing and Subgrid-Scale Variability of Density Profiles on the Determination of Mixed Layer Depth

2017 ◽  
Vol 34 (9) ◽  
pp. 2083-2101 ◽  
Author(s):  
Hyejin Ok ◽  
Yign Noh ◽  
Yeonju Choi
Keyword(s):  
Mixed Layer ◽  
General Circulation ◽  
Mixed Layer Depth ◽  
Global Ocean ◽  
Observation Data ◽  
Subgrid Scale ◽  
Layer Depth ◽  
Profile Error ◽  
Density Profiles

AbstractThis study investigates how pycnocline smoothing and subgrid-scale variability of density profiles influence the determination of the mixed layer depth (MLD) in the global ocean, and applies the results of analysis to assess the ability of ocean general circulation models (OGCM) to simulate the MLD. For this purpose, individual, monthly mean, and climatological profiles are analyzed over a horizontal resolution of 1° × 1° for both observation data (Argo) and eddy-resolving OGCM (OFES) results. It is found that the MLDs from averaged profiles are generally smaller than those from individual profiles because of pycnocline smoothing induced by the averaging process. A correlation is found between the decrease in MLD Δh and the increase in pycnocline thickness Δδ of averaged profiles, except during winter in the high-latitude ocean. The relation is estimated as Δh = −αΔδ − β, where α ≃ 0.7 in all cases, but β increases with the subgrid-scale variability of density profiles. A correlation is also found between Δh and the standard deviation of the MLD within a grid. The results are applied to estimate how much of the MLD bias of OFES is due to prediction error and how much is due to profile error, induced by different pycnocline smoothing and the subgrid-scale variability of density profiles. The study also shows how profile error varies with the threshold density difference criterion.

scholarly journals Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

2020 ◽  
Author(s):  
Wei-Lei Wang ◽  
Guisheng Song ◽  
François Primeau ◽  
Eric S. Saltzman ◽  
Thomas G. Bell ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solar Radiation ◽  
Mixed Layer ◽  
Dimethyl Sulfide ◽  
Mixed Layer Depth ◽  
Environmental Parameters ◽  
Global Scale ◽  
Global Ocean ◽  
Layer Depth

Abstract. Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. However, a knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to understand the factors controlling surface ocean DMS and its impact on climate. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 57 810 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of lat-lon coordinates, time-of-day, time-of-year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, silicate, and oxygen. Linear regressions of DMS against the environmental parameters show that on a global scale mixed layer depth and solar radiation are the strongest predictors of DMS, however, they capture 14 % and 12 % of the raw DMS data variance, respectively. The multi-linear regression can capture more (∼29 %) of the raw data variance, but strongly underestimates high DMS concentrations. In contrast, the ANN captures ~61 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in DMS concentration and sea-to-air flux. The highest concentrations (fluxes) occur in the high-latitude oceans during the summer. We estimate a lower global sea-to-air DMS flux (17.90 ± 0.34 Tg S yr−1) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used.

Variability of the Oceanic Mixed Layer, 1960–2004

2008 ◽  
Vol 21 (5) ◽  
pp. 1029-1047 ◽  
Author(s):  
James A. Carton ◽  
Semyon A. Grodsky ◽  
Hailong Liu
Keyword(s):  
Mixed Layer ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Mixed Layer Depth ◽  
Global Ocean ◽  
Boreal Summer ◽  
Layer Depth ◽  
The North ◽  
The North Atlantic ◽  
Mixed Layers

Abstract A new monthly uniformly gridded analysis of mixed layer properties based on the World Ocean Atlas 2005 global ocean dataset is used to examine interannual and longer changes in mixed layer properties during the 45-yr period 1960–2004. The analysis reveals substantial variability in the winter–spring depth of the mixed layer in the subtropics and midlatitudes. In the North Pacific an empirical orthogonal function analysis shows a pattern of mixed layer depth variability peaking in the central subtropics. This pattern occurs coincident with intensification of local surface winds and may be responsible for the SST changes associated with the Pacific decadal oscillation. Years with deep winter–spring mixed layers coincide with years in which winter–spring SST is low. In the North Atlantic a pattern of winter–spring mixed layer depth variability occurs that is not so obviously connected to local changes in winds or SST, suggesting that other processes such as advection are more important. Interestingly, at decadal periods the winter–spring mixed layers of both basins show trends, deepening by 10–40 m over the 45-yr period of this analysis. The long-term mixed layer deepening is even stronger (50–100 m) in the North Atlantic subpolar gyre. At tropical latitudes the boreal winter mixed layer varies in phase with the Southern Oscillation index, deepening in the eastern Pacific and shallowing in the western Pacific and eastern Indian Oceans during El Niños. In boreal summer the mixed layer in the Arabian Sea region of the western Indian Ocean varies in response to changes in the strength of the southwest monsoon.

An analytical model for remote sensing determination of the mixed layer depth

1991 ◽  
Vol 38 (3) ◽  
pp. 267-287 ◽  
Author(s):  
Xiao-Hai Yan ◽  
A. Okubo ◽  
J.R. Schubel ◽  
D.W. Pritchard
Keyword(s):  
Remote Sensing ◽  
Analytical Model ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Layer Depth

scholarly journals Buoyancy-Forced Downwelling in Boundary Currents

2008 ◽  
Vol 38 (12) ◽  
pp. 2704-2721 ◽  
Author(s):  
Michael A. Spall
Keyword(s):  
Boundary Layer ◽  
Wave Propagation ◽  
Heat Loss ◽  
Mixed Layer ◽  
General Circulation ◽  
Mixed Layer Depth ◽  
Kelvin Wave ◽  
Surface Cooling ◽  
Layer Depth ◽  
Boundary Currents

Abstract The issue of downwelling resulting from surface buoyancy loss in boundary currents is addressed using a high-resolution, nonhydrostatic numerical model. It is shown that the net downwelling is determined by the change in the mixed layer density along the boundary. For configurations in which the density on the boundary increases in the direction of Kelvin wave propagation, there is a net downwelling within the domain. For cases in which the density decreases in the direction of Kelvin wave propagation, cooling results in a net upwelling within the domain. Symmetric instability within the mixed layer drives an overturning cell in the interior, but it does not contribute to the net vertical motion. The net downwelling is determined by the geostrophic flow toward the boundary and is carried downward in a very narrow boundary layer of width E1/3, where E is the Ekman number. For the calculations here, this boundary layer is O(100 m) wide. A simple model of the mixed layer temperature that balances horizontal advection with surface cooling is used to predict the net downwelling and its dependence on external parameters. This model shows that the net sinking rate within the domain depends not only on the amount of heat loss at the surface but also on the Coriolis parameter, the mixed layer depth (or underlying stratification), and the horizontal velocity. These results indicate that if one is to correctly represent the buoyancy-forced downwelling in general circulation models, then it is crucial to accurately represent the velocity and mixed layer depth very close to the boundary. These results also imply that processes that lead to weak mixing within a few kilometers of the boundary, such as ice formation or freshwater runoff, can severely limit the downwelling forced by surface cooling, even if there is strong heat loss and convection farther offshore.

The Vertical Structure of Eddy Heat Transport Simulated by an Eddy-Resolving OGCM

2010 ◽  
Vol 40 (2) ◽  
pp. 340-353 ◽  
Author(s):  
Bo Young Yim ◽  
Yign Noh ◽  
Bo Qiu ◽  
Sung Hyup You ◽  
Jong Hwan Yoon
Keyword(s):  
Heat Transport ◽  
Mixed Layer ◽  
General Circulation ◽  
Vertical Structure ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Spatial And Temporal Variation ◽  
Observation Data ◽  
Eddy Heat Transport

Abstract The vertical structure of meridional eddy heat transport (EHT) of the North Pacific was investigated by analyzing the results from an eddy-resolving ocean general circulation model (OGCM) with a horizontal resolution of , while comparing with previous simulation results and observation data. In particular, the spatial and temporal variation of the effective depth of EHT He was investigated, which is defined by the depth integrated EHT (D-EHT) divided by EHT at the surface. It was found that the annual mean value of He is proportional to the eddy kinetic energy (EKE) level at the surface in general. However, its seasonal variation is controlled by the mixed layer depth (MLD) in the extratropical ocean (>20°N). Examination of the simulated eddy structures reveals that the temperature associated with mesoscale eddies is radically modified by the surface forcing in the mixed layer, while the velocity field is not, and the consequent enhanced misalignment of temperature and velocity anomalies leads to the radical change of EHT across the seasonal thermocline.

scholarly journals Intercomparison and validation of the mixed layer depth fields of global ocean syntheses

2015 ◽  
Vol 49 (3) ◽  
pp. 753-773 ◽  
Author(s):  
Takahiro Toyoda ◽  
Yosuke Fujii ◽  
Tsurane Kuragano ◽  
Masafumi Kamachi ◽  
Yoichi Ishikawa ◽  
...  
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Global Ocean ◽  
Layer Depth
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