Deep convection in the Lofoten Basin: ARGO vs MITgcm

2020 ◽  
Author(s):  
Aleksandr Fedorov ◽  
Belonenko Tatyana
Keyword(s):  
Mixed Layer ◽  
Water Mass ◽  
Deep Convection ◽  
Mixed Layer Depth ◽  
Intermediate Water ◽  
Model Data ◽  
Layer Depth ◽  
Russian Science ◽  
Intermediate Water Mass

<p>The Lofoten basin (the LB) contains relatively warm and salty waters regarding border basins such as Greenland and Barents Seas. Variability of the processes inside occurring in the basin reflects on the climate as on the mesoscales as on the interannual scales. We use a term mixed layer depth (MLD) as a border of the pycnocline in the water column, this parameter lets us evaluate the intensity of the convection in the region. Several methods of MLD calculations are tested in the current study: Kara, Montegut, and Dukhovskoy. The convection in the basin destructs stratification and forms massive intermediate water mass. The MITgcm data for 1993-2012 and over 5000 in-situ Argo T, S profiles for 2001-2017 were used in the calculations of the MLD.</p><p>We consider the maximum MLD (mMLD) in the region and its spatial distribution. The mMLD is higher in the central part of the LB and corresponds to the location of the Lofoten basin eddy (the LBE). Here the mMLD reaches 1000 meters, the medium maximum is 400 meters based both on the in-situ and model data. The maximum mixed layer depth ​​varies in the range of 400-1000 meters according to both datasets were used. The MLD over 400 meters is observed from January to May every year.</p><p><strong>Acknowledgments: </strong>The authors acknowledge the support of the Russian Science Foundation (project No. 18-17-00027). The results of the MITgcm were provided by D.L. Volkov, Cooperative Institute for Marine and Atmospheric Studies, University of Miami, USA.</p>

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

Climatology of mixed layer depth in the Gulf of Aden derived from in situ temperature profiles

2019 ◽  
Vol 75 (4) ◽  
pp. 335-347 ◽  
Author(s):  
Cheriyeri P. Abdulla ◽  
Mohammed A. Alsaafani ◽  
Turki M. Alraddadi ◽  
Alaa M. Albarakati
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Temperature Profiles ◽  
Gulf Of Aden ◽  
Layer Depth

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 Mixed layer variability and chlorophyll <i>a</i> biomass in the Bay of Bengal

2014 ◽  
Vol 11 (14) ◽  
pp. 3819-3843 ◽  
Author(s):  
J. Narvekar ◽  
S. Prasanna Kumar
Keyword(s):  
Mixed Layer ◽  
Bay Of Bengal ◽  
Mixed Layer Depth ◽  
Remote Sensing Data ◽  
Ekman Pumping ◽  
Layer Depth ◽  
Basin Scale ◽  
Deep Mixed Layer ◽  
Northern Bay Of Bengal

Abstract. The mixed layer is the most variable and dynamically active part of the marine environment that couples the underlying ocean to the atmosphere and plays an important role in determining the oceanic primary productivity. We examined the basin-scale processes controlling the seasonal variability of mixed layer depth in the Bay of Bengal and its association with chlorophyll using a suite of in situ as well as remote sensing data. A coupling between mixed layer depth and chlorophyll was seen during spring intermonsoon and summer monsoon, but for different reasons. In spring intermonsoon the temperature-dominated stratification and associated shallow mixed layer makes the upper waters of the Bay of Bengal nutrient depleted and oligotrophic. In summer, although the salinity-dominated stratification in the northern Bay of Bengal shallows the mixed layer, the nutrient input from adjoining rivers enhance the surface chlorophyll. This enhancement is confined only to the surface layer and with increase in depth, the chlorophyll biomass decreases rapidly due to reduction in sunlight by suspended sediment. In the south, advection of high salinity waters from the Arabian Sea and westward propagating Rossby waves from the eastern Bay of Bengal led to the formation of deep mixed layer. In contrast, in the Indo–Sri Lanka region, the shallow mixed layer and nutrient enrichment driven by upwelling and Ekman pumping resulted in chlorophyll enhancement. The mismatch between the nitrate and chlorophyll indicated the inadequacy of present data to fully unravel its coupling to mixed layer processes.

scholarly journals Has Sverdrup's critical depth hypothesis been tested? Mixed layers vs. turbulent layers

2014 ◽  
Vol 72 (6) ◽  
pp. 1897-1907 ◽  
Author(s):  
Peter J. S. Franks
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Critical Depth ◽  
Layer Depth ◽  
Poor Indicator ◽  
Active Turbulence ◽  
Mixed Layers ◽  
Vertical Scales ◽  
Over Time

Abstract Sverdrup (1953. On conditions for the vernal blooming of phytoplankton. Journal du Conseil International pour l'Exploration de la Mer, 18: 287–295) was quite careful in formulating his critical depth hypothesis, specifying a “thoroughly mixed top layer” with mixing “strong enough to distribute the plankton organisms evenly through the layer”. With a few notable exceptions, most subsequent tests of the critical depth hypothesis have ignored those assumptions, using estimates of a hydrographically defined mixed-layer depth as a proxy for the actual turbulence-driven movement of the phytoplankton. However, a closer examination of the sources of turbulence and stratification in turbulent layers shows that active turbulence is highly variable over time scales of hours, vertical scales of metres, and horizontal scales of kilometres. Furthermore, the mixed layer as defined by temperature or density gradients is a poor indicator of the depth or intensity of active turbulence. Without time series of coincident, in situ measurements of turbulence and phytoplankton rates, it is not possible to properly test Sverdrup's critical depth hypothesis.

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

Mixed layer depth calculation in deep convection regions in ocean numerical models

2017 ◽  
Vol 120 ◽  
pp. 60-78 ◽  
Author(s):  
Peggy Courtois ◽  
Xianmin Hu ◽  
Clark Pennelly ◽  
Paul Spence ◽  
Paul G. Myers
Keyword(s):  
Mixed Layer ◽  
Numerical Models ◽  
Deep Convection ◽  
Mixed Layer Depth ◽  
Layer Depth

scholarly journals Lateral Heat Exchange after the Labrador Sea Deep Convection in 2008

2014 ◽  
Vol 44 (12) ◽  
pp. 2991-3007 ◽  
Author(s):  
Weiwei Zhang ◽  
Xiao-Hai Yan
Keyword(s):  
Heat Flux ◽  
Mixed Layer ◽  
Deep Convection ◽  
Mixed Layer Depth ◽  
Labrador Sea ◽  
Boundary Current ◽  
Strong Fluctuation ◽  
Layer Depth ◽  
Ensemble Mean ◽  
Lateral Heat

Abstract The mechanisms through which convected water restratifies in the Labrador Sea are still under debate. The Labrador Sea restratification after deep convection in the 2007/08 winter is studied with an eddy-resolving numerical model. The modeled mixed layer depth during wintertime resembles the Argo observed mixed layer very well, and the lateral heat flux during the subsequent restratification is in line with observations. The Irminger rings (IRs) are reproduced with fresher caps above the 300-m depths, and they are identified and tracked automatically. The model underestimates both the number of IRs in the convection area and the heat they carry. The underestimation is most likely caused by the errors in the direction of the west Greenland currents in the model, which causes more IRs propagating westward, and only the IRs originating south of 61.5°N are able to propagate southward, yet with speed much slower than observed speed. The model still observed three eddies propagating into the convection area during the restratification phase in 2008, and their thermal contribution ranges from 1% to 4% if the estimation is made at the time when they enter the convection area. If all newly generated eddies are considered, then the ensemble-mean contributions by the IRs become 5.3%. The more detailed and direct heat flux by IRs is difficult to derive because of the strong fluctuation of the identified eddy radius. Nevertheless, the modeled lateral heat flux is largely composed of the boundary current eddies and convective eddies, thus it is possible for the model to maintain an acceptable thermal balance.

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