Coupled Ocean–Atmosphere Covariances in Global Ensemble Simulations: Impact of an Eddy-Resolving Ocean

2021 ◽  
Vol 149 (5) ◽  
pp. 1193-1209
Author(s):  
Sergey Frolov ◽  
Carolyn A. Reynolds ◽  
Michael Alexander ◽  
Maria Flatau ◽  
Neil P. Barton ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Indian Ocean ◽  
Warm Pool ◽  
Coupled Processes ◽  
Global Ocean ◽  
Atmospheric Convection ◽  
Ocean Atmosphere ◽  
Short Term Forecasting

AbstractPatterns of correlations between the ocean and the atmosphere are examined using a high-resolution (1/12° ocean and ice, 1/3° atmosphere) ensemble of data assimilative, coupled, global, ocean–atmosphere forecasts. This provides a unique perspective into atmosphere–ocean interactions constrained by assimilated observations, allowing for the contrast of patterns of coupled processes across regions and the examination of processes affected by ocean mesoscale eddies. Correlations during the first 24 h of the coupled forecast between the ocean surface temperature and atmospheric variables, and between the ocean mixed layer depth and surface winds are examined as a function of region and season. Three distinct coupling regimes emerge: 1) regions characterized by strong sea surface temperature fronts, where uncertainty in the ocean mesoscale influences ocean–atmosphere exchanges; 2) regions with intense atmospheric convection over the tropical oceans, where uncertainty in the modeled atmospheric convection impacts the upper ocean; and 3) regions where the depth of the seasonal mixed layer (MLD) determines the magnitude of the coupling, which is stronger when the MLD is shallow and weaker when the MLD is deep. A comparison with models at lower horizontal (1/12° vs 1° and 1/4°) and vertical (1- vs 10-m depth of the first layer) ocean resolution reveals that coupling in the boundary currents, the tropical Indian Ocean, and the warm pool regions requires high levels of horizontal and vertical resolution. Implications for coupled data assimilation and short-term forecasting are discussed.

Interannual variability of the Tropical Indian Ocean mixed layer depth

2012 ◽  
Vol 40 (3-4) ◽  
pp. 743-759 ◽  
Author(s):  
M. G. Keerthi ◽  
M. Lengaigne ◽  
J. Vialard ◽  
C. de Boyer Montégut ◽  
P. M. Muraleedharan
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Indian Ocean ◽  
Ocean Mixed Layer ◽  
Layer Depth ◽  
Ocean Mixed Layer Depth

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 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.

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.

scholarly journals Contributions of Indian Ocean and Monsoon Biases to the Excessive Biennial ENSO in CCSM3

2009 ◽  
Vol 22 (7) ◽  
pp. 1850-1858 ◽  
Author(s):  
Jin-Yi Yu ◽  
Fengpeng Sun ◽  
Hsun-Ying Kao
Keyword(s):  
Indian Ocean ◽  
Southern Oscillation ◽  
Surface Wind ◽  
Tropical Indian Ocean ◽  
Global Ocean ◽  
Climate System Model ◽  
Wind Pattern ◽  
Enso Variability ◽  
Monsoon Variability ◽  
Ocean Atmosphere

Abstract The Community Climate System Model, version 3 (CCSM3), is known to produce many aspects of El Niño–Southern Oscillation (ENSO) realistically, but the simulated ENSO exhibits an overly strong biennial periodicity. Hypotheses on the cause of this excessive biennial tendency have thus far focused primarily on the model’s biases within the tropical Pacific. This study conducts CCSM3 experiments to show that the model’s biases in simulating the Indian Ocean mean sea surface temperatures (SSTs) and the Indian and Australian monsoon variability also contribute to the biennial ENSO tendency. Two CCSM3 simulations are contrasted: a control run that includes global ocean–atmosphere coupling and an experiment in which the air–sea coupling in the tropical Indian Ocean is turned off by replacing simulated SSTs with an observed monthly climatology. The decoupling experiment removes CCSM3’s warm bias in the tropical Indian Ocean and reduces the biennial variability in Indian and Australian monsoons by about 40% and 60%, respectively. The excessive biennial ENSO is found to reduce dramatically by about 75% in the decoupled experiment. It is shown that the biennial monsoon variability in CCSM3 excites an anomalous surface wind pattern in the western Pacific that projects well into the wind pattern associated with the onset phase of the simulated biennial ENSO. Therefore, the biennial monsoon variability is very effective in exciting biennial ENSO variability in CCSM3. The warm SST bias in the tropical Indian Ocean also increases ENSO variability by inducing stronger mean surface easterlies along the equatorial Pacific, which strengthen the Pacific ocean–atmosphere coupling and enhance the ENSO intensity.

scholarly journals Ocean–Atmosphere Coupling in the Monsoon Intraseasonal Oscillation: A Simple Model Study

2008 ◽  
Vol 21 (20) ◽  
pp. 5254-5270 ◽  
Author(s):  
Gilles Bellon ◽  
Adam H. Sobel ◽  
Jerome Vialard
Keyword(s):  
Mixed Layer ◽  
Bay Of Bengal ◽  
Mixed Layer Depth ◽  
Intraseasonal Oscillation ◽  
Thermal Inertia ◽  
Coupled Model ◽  
Boreal Winter ◽  
Quasi Equilibrium ◽  
Layer Depth ◽  
Ocean Atmosphere

Abstract A simple coupled model is used in a zonally symmetric aquaplanet configuration to investigate the effect of ocean–atmosphere coupling on the Asian monsoon intraseasonal oscillation. The model consists of a linear atmospheric model of intermediate complexity based on quasi-equilibrium theory coupled to a simple, linear model of the upper ocean. This model has one unstable eigenmode with a period in the 30–60-day range and a structure similar to the observed northward-propagating intraseasonal oscillation in the Bay of Bengal/west Pacific sector. The ocean–atmosphere coupling is shown to have little impact on either the growth rate or latitudinal structure of the atmospheric oscillation, but it reduces the oscillation’s period by a quarter. At latitudes corresponding to the north of the Indian Ocean, the sea surface temperature (SST) anomalies lead the precipitation anomalies by a quarter of a period, similarly to what has been observed in the Bay of Bengal. The mixed layer depth is in phase opposition to the SST: a monsoon break corresponds to both a warming and a shoaling of the mixed layer. This behavior results from the similarity between the patterns of the predominant processes: wind-induced surface heat flux and wind stirring. The instability of the seasonal monsoon flow is sensitive to the seasonal mixed layer depth: the oscillation is damped when the oceanic mixed layer is thin (about 10 m deep or thinner), as in previous experiments with several models aimed at addressing the boreal winter Madden–Julian oscillation. This suggests that the weak thermal inertia of land might explain the minima of intraseasonal variance observed over the Asian continent.

scholarly journals Role of North Pacific Mixed Layer in the Response of SST Annual Cycle to Global Warming

2015 ◽  
Vol 28 (23) ◽  
pp. 9451-9458 ◽  
Author(s):  
Changlin Chen ◽  
Guihua Wang
Keyword(s):  
Global Warming ◽  
Mixed Layer ◽  
Annual Cycle ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Mixed Layer Depth ◽  
Ecological Impacts ◽  
Global Ocean ◽  
The North ◽  
The North Pacific

Abstract The annual cycle of sea surface temperature (SST) in the North Pacific Ocean is examined in terms of its response to global warming based on climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). As the global ocean warms up, the SST in the North Pacific generally tends to increase and the warming is greater in summer than in winter, leading to a significant intensification of SST annual cycle. The mixed layer temperature equation is used to examine the mechanism of this intensification. Results show that the decrease of mixed layer depth (MLD) in summer is the main reason behind the intensification of SST annual cycle. Because the MLD in summer is much shallower than that in winter, the incoming net heat flux is trapped in a thinner surface layer in summer, causing a warmer summer SST and the amplification of SST annual cycle. The change of the SST annual cycle in the North Pacific may have profound ecological impacts.

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