scholarly journals Observed and Modelled Mixed-Layer Properties on the Continental Shelf of Sardinia (Mediterranean Sea)

2016 ◽  
Author(s):  
Reiner Onken
Keyword(s):  
Boundary Conditions ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Mixed Layer Depth ◽  
Vertical Mixing ◽  
Global Ocean ◽  
Surface Boundary ◽  
Regional Ocean Modeling System ◽  
Layer Depth ◽  
Mixed Layer Temperature

Abstract. The Regional Ocean Modeling System (ROMS) has been employed to explore the sensitivity of the forecast skill of mixed-layer properties to the initial conditions, boundary conditions, and vertical mixing parameterisations. The initial and lateral boundary conditions were provided by the Mediterranean Forecasting System (MFS) or by the MERCATOR global ocean circulation model via one-way nesting; the initial conditions were additionally updated by the assimilation of observations. Nowcasts and forecasts from the weather forecast models COSMO-ME and COSMO-IT, partly melded with observations, served as surface boundary conditions. The vertical mixing was parameterised by the GLS (Generic Length Scale) scheme (Umlauf et al. 2003) in four different setups. All ROMS forecasts were validated against observations which were taken during the REP14-MED oceanographic survey to the west of Sardinia. Nesting ROMS in MERCATOR and updating the initial conditions by data assimilation provided the best agreement of the predicted mixed-layer temperature and the mixed-layer depth with time series from a moored thermistor chain. Further improvement was obtained by the usage of COSMO-ME atmospheric forcing which was melded with real observations, and by the application of the k − ε vertical mixing scheme with increased vertical eddy diffusivity. The predicted temporal variability of the mixed-layer temperature was reasonably well correlated with the observed variability in the frequency range above one cycle per day, while the modelled variability of the mixed-layer depth exhibited only agreement with the observations near the diurnal frequency peak. For the forecasted horizontal variability, reasonable agreement was found with observations from a ScanFish section, but only for the mesoscale wavenumber band; the observed sub-mesoscale variability was not reproduced by ROMS.

scholarly journals Validation of an ocean shelf model for the prediction of mixed-layer properties in the Mediterranean Sea west of Sardinia

Ocean Science ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 235-257 ◽  
Author(s):  
Reiner Onken
Keyword(s):  
Boundary Conditions ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Mixed Layer Depth ◽  
Vertical Mixing ◽  
Global Ocean ◽  
Wave Number ◽  
Surface Boundary ◽  
Regional Ocean Modeling System ◽  
The Mediterranean

Abstract. The Regional Ocean Modeling System (ROMS) has been employed to explore the sensitivity of the forecast skill of mixed-layer properties to initial conditions, boundary conditions, and vertical mixing parameterisations. The initial and lateral boundary conditions were provided by the Mediterranean Forecasting System (MFS) or by the MERCATOR global ocean circulation model via one-way nesting; the initial conditions were additionally updated through the assimilation of observations. Nowcasts and forecasts from the weather forecast models COSMO-ME and COSMO-IT, partly melded with observations, served as surface boundary conditions. The vertical mixing was parameterised by the GLS (generic length scale) scheme Umlauf and Burchard (2003) in four different set-ups. All ROMS forecasts were validated against the observations which were taken during the REP14-MED survey to the west of Sardinia. Nesting ROMS in MERCATOR and updating the initial conditions through data assimilation provided the best agreement of the predicted mixed-layer properties with the time series from a moored thermistor chain. Further improvement was obtained by the usage of COSMO-ME atmospheric forcing, which was melded with real observations, and by the application of the k-ω vertical mixing scheme with increased vertical eddy diffusivity. The predicted temporal variability of the mixed-layer temperature was reasonably well correlated with the observed variability, while the modelled variability of the mixed-layer depth exhibited only agreement with the observations near the diurnal frequency peak. For the forecasted horizontal variability, reasonable agreement was found with observations from a ScanFish section, but only for the mesoscale wave number band; the observed sub-mesoscale variability was not reproduced by ROMS.

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.

scholarly journals Decadal to Multidecadal Variability of the Mixed Layer to the South of the Kuroshio Extension Region

2020 ◽  
Vol 33 (17) ◽  
pp. 7697-7714
Author(s):  
Baolan Wu ◽  
Xiaopei Lin ◽  
Lisan Yu
Keyword(s):  
Heat Flux ◽  
Pacific Ocean ◽  
Mixed Layer ◽  
Kuroshio Extension ◽  
Mixed Layer Depth ◽  
Layer Depth ◽  
Multidecadal Variability ◽  
Mixed Layer Temperature ◽  
The Kuroshio ◽  
The Western Pacific

AbstractThe decadal to multidecadal mixed layer variability is investigated in a region south of the Kuroshio Extension (130°E–180°, 25°–35°N), an area where the North Pacific subtropical mode water forms, during 1948–2012. By analyzing the mixed layer heat budget with different observational and reanalysis data, here we show that the decadal to multidecadal variability of the mixed layer temperature and mixed layer depth is covaried with the Atlantic multidecadal oscillation (AMO), instead of the Pacific decadal oscillation (PDO). The mixed layer temperature has strong decadal to multidecadal variability, being warm before 1970 and after 1990 (AMO positive phase) and cold during 1970–90 (AMO negative phase), and so does the mixed layer depth. The dominant process for the mixed layer temperature decadal to multidecadal variability is the Ekman advection, which is controlled by the zonal wind changes related to the AMO. The net heat flux into the ocean surface Qnet acts as a damping term and it is mainly from the effect of latent heat flux and partially from sensible heat flux. While the wind as well as mixed layer temperature decadal changes related to the PDO are weak in the western Pacific Ocean. Our finding proposes the possible influence of the AMO on the northwestern Pacific Ocean mixed layer variability, and could be a potential predictor for the decadal to multidecadal climate variability in the western Pacific Ocean.

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.

Decadal Variation in Winter Mixed Layer Depth South of the Kuroshio Extension and Its Influence on Winter Mixed Layer Temperature

2016 ◽  
Vol 29 (3) ◽  
pp. 1237-1252 ◽  
Author(s):  
Shusaku Sugimoto ◽  
Shin’ichiro Kako
Keyword(s):  
Mixed Layer ◽  
North Pacific ◽  
Kuroshio Extension ◽  
Mixed Layer Depth ◽  
Positive Anomaly ◽  
Surface Cooling ◽  
Layer Depth ◽  
Mixed Layer Temperature ◽  
Winter Mixed Layer ◽  
The Kuroshio

Abstract The long-term behavior of the wintertime mixed layer depth (MLD) and mixed layer temperature (MLT) are investigated in a region south of the Kuroshio Extension (KE) (30°–37°N, 141°–155°E), an area of the North Pacific subtropical gyre where the deepest MLD occurs, using historical temperature profiles of 1968–2014. Both the MLD and MLT in March have low-frequency variations, which show significant decadal (~10 yr) variations after the late 1980s. Observational data and simulation outputs from a one-dimensional turbulent closure model reveal that surface cooling is the main control on winter MLD in the late 1970s and 1980s, whereas there is a change in the strength of subsurface stratification is the main control after ~1990. In the latter period, a weak (strong) subsurface stratification is caused by a straight path (convoluted path) of the KE and by a deepening (shallowing) of the main thermocline depth due to oceanic Rossby waves formed as a result of positive (negative) anomalies of wind stress curl associated with a southward (northward) movement of the Aleutian low in the central North Pacific. During deeper (shallower) periods of winter MLD, the strong (weak) vertical entrainment process, resulting from a rapid (slow) deepening of the mixed layer (ML) in January and February, forms a negative (positive) anomaly of temperature tendency. Consequently, the decadal variations in wintertime MLT are formed.

In Situ Observations of Madden–Julian Oscillation Mixed Layer Dynamics in the Indian and Western Pacific Oceans

2012 ◽  
Vol 25 (7) ◽  
pp. 2306-2328 ◽  
Author(s):  
Kyla Drushka ◽  
Janet Sprintall ◽  
Sarah T. Gille ◽  
Susan Wijffels
Keyword(s):  
Heat Flux ◽  
Indian Ocean ◽  
Mixed Layer ◽  
Heat Budget ◽  
Mixed Layer Depth ◽  
Layer Depth ◽  
Temperature Variations ◽  
Central Indian Ocean ◽  
Mixed Layer Temperature

Abstract The boreal winter response of the ocean mixed layer to the Madden–Julian oscillation (MJO) in the Indo-Pacific region is determined using in situ observations from the Argo profiling float dataset. Composite averages over numerous events reveal that the MJO forces systematic variations in mixed layer depth and temperature throughout the domain. Strong MJO mixed layer depth anomalies (>15 m peak to peak) are observed in the central Indian Ocean and in the far western Pacific Ocean. The strongest mixed layer temperature variations (>0.6°C peak to peak) are found in the central Indian Ocean and in the region between northwest Australia and Java. A heat budget analysis is used to evaluate which processes are responsible for mixed layer temperature variations at MJO time scales. Though uncertainties in the heat budget are on the same order as the temperature trend, the analysis nonetheless demonstrates that mixed layer temperature variations associated with the canonical MJO are driven largely by anomalous net surface heat flux. Net heat flux is dominated by anomalies in shortwave and latent heat fluxes, the relative importance of which varies between active and suppressed MJO conditions. Additionally, rapid deepening of the mixed layer in the central Indian Ocean during the onset of active MJO conditions induces significant basin-wide entrainment cooling. In the central equatorial Indian Ocean, MJO-induced variations in mixed layer depth can modulate net surface heat flux, and therefore mixed layer temperature variations, by up to ~40%. This highlights the importance of correctly representing intraseasonal mixed layer depth variations in climate models in order to accurately simulate mixed layer temperature, and thus air–sea interaction, associated with the MJO.

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

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.

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