Modular Ocean Model Version Research Articles

Detecting Instantaneous Tidal Signals in Ocean Models Utilizing Streaming Band‐Pass Filters

AbstractThrough the implementation of a streaming filter, output of numerical ocean simulations can be band‐pass filtered at tidal frequencies while the model is running, yielding time series of sinusoidal motions consisting of tidal signals in the filter's target frequency band. The filtering algorithm is developed from a system of two ordinary differential equations that represents the motion of a damped harmonic oscillator. The filter's response to a broadband input signal is unity at its target frequency but vanishes toward the low and high frequency limits. The decay of the filter response is controlled by a dimensionless parameter, which determines the filter's bandwidth. As a result, the filter allows signals within a small frequency band around its target frequency to pass through, while blocking signals outside of its target frequency band. In this work, the filtering algorithm is implemented into the barotropic solver of the Modular Ocean Model version 6 (MOM6) for determining the instantaneous tidal velocities of the semi‐diurnal and diurnal tides. Utilizing the filters, the frequency‐dependent internal wave drag is applied to the semi‐diurnal and diurnal frequency bands separately. The simulation results suggest that the performance of the algorithm is consistent with the filter transfer function in Fourier space. Potential applications of the algorithm also include de‐tiding the model output for nested regional ocean models, especially those for the purpose of operational forecasting.

Improving Global Barotropic Tides With Sub‐Grid Scale Topography

AbstractIn recent years, efforts have been made to include tides in both operational ocean models as well as climate and earth system models. The accuracy of the barotropic tides is often limited by the model topography, which is in turn limited by model horizontal resolution. In this work, we explore the reduction of barotropic tidal errors in an ocean general circulation model (Modular Ocean Model version 6; MOM6) using sub‐grid scale topography representation. We follow the methodology from Adcroft (2013, https://doi.org/10.1016/j.ocemod.2013.03.002), which utilizes statistics from finer resolution topographic data sets to represent sub‐grid scale features with a light computational cost in a structured finite volume formulation. The geometric effect from sub‐grid scale topography can be introduced to the model with only a few parameters at each grid cell. The porous barriers, which are implemented at the walls of the grid cells, are used to modify transport between grid cells. Our results show that the globally averaged tidal error in lower‐resolution simulations is significantly reduced with the use of porous barriers. We argue this method is a potentially useful tool to improve simulations of tides (and other flows) in low‐resolution simulations.

Origin and pathway of a subsurface maximum of 137Cs detected in the winter of 2012 after the Fukushima accident

This study investigates the dispersion behavior of 137Cs and evaluates its origin (atmospheric deposition or direct ocean release) from the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident using a Lagrangian particle tracking model. The ocean circulation fields based on the Modular Ocean Model Version 5 (MOM5) were adopted for the simulation. The MOM5 results represented the formation and migration of subtropical mode water (STMW) comparable with observations and reanalysis data. Particularly, anticyclonic eddies south of the Kuroshio extension promoted surface mixing over 300 m in the cooling season. The particle tracking simulation reproduced well the maximum subsurface activity between 142 and 146°E, where STMW is deep owing to anticyclonic eddies, compared to the activity found via measurements conducted around 149°E in the winter of 2012. It also demonstrated that the 137Cs of the tropical and subtropical regions (10–35°N, 142–146°E) in the winter of 2012 almost entirely originated from atmospheric deposition.

Analysis of Drought Characteristics Projections for the Tibetan Plateau Based on the GFDL-ESM2M Climate Model

Under conditions of continuous global warming, research into the future change trends of regional dry-wet climates is key for coping with and adapting to climate change, and is also an important topic in the field of climate change prediction. In this study, daily precipitation and mean temperature datasets under four representative concentrative pathway (RCP) scenarios in the geophysical fluid dynamics laboratory Earth system model with modular ocean model (GFDL-ESM2M) version 4 were used to calculate the standardized precipitation-evapotranspiration index of the Tibetan Plateau (TP) at different time scales. Using a multi-analytical approach including the Mann–Kendall trend test and run theory, the spatiotemporal variation characteristics of drought in the TP from 2016 to 2099 were studied. The results show that the overall future climate of the TP will develop towards warm and humid, and that the monthly-scale wet–dry changes will develop non-uniformly. As the concentration of carbon dioxide emissions increases in the future, the proportion of extremely significant aridification and humidification areas in the TP will significantly increase, and the possibility of extreme disasters will also increase. Moreover, influenced by the increase of annual TP precipitation, the annual scale of future drought in the region will tend to decrease slightly, and the spatial distributions of the frequency and intensity of droughts at all levels will develop uniformly. Under all four RCP scenarios, the drought duration of the TP was mainly less than 3 months, and the drought cycle in the southern region was longer than that in the northern region. The results of this study provide a new basis for the development of adaptive measures for the TP to cope with climate change.

A modified thermodynamic sea ice model and its application

A modified thermodynamic sea ice model suitable for large-scale climate simulations is described. Originated from the Winton’s three-layer model framework, this new model includes several improvements in the vertical thermodynamics: (1) the number of ice layers increases from two to three; (2) the snow heat capacity is included; (3) a vertically varying salinity profile is implemented; and (4) a temperature- and salinity-dependent heat conductivity parameterization scheme is introduced. A non-iterative fully implicit time-stepping scheme similar to Winton’s model is used to calculate the temperature of ice and snow. Results from a series of one-dimensional experiments show that equilibrium ice thickness in the modified model is increased by 45 cm when compared with the original Winton’s model. All modifications mentioned above contribute to this change of ice thickness, among which the increase of ice layer has the most significant effect. Experiments using the Modular Ocean Model version 4 (MOM4) coupled with the modified model show an improved sea ice simulation which includes an increase in both the sea ice volume and thickness over the entire Arctic region, confirming the above founding. However, contrary model behavior exhibits when the snow heat capacity is considered that warrants further investigation.

A Comparative Study of Vertical Mixing Schemes in Modeling the Bay of Bengal Dynamics

AbstractThe choice of vertical mixing scheme in ocean models plays an important role in modeling the surface and subsurface circulation and the vertical structure. This work performs a comparative study between K‐profile parametrization (KPP) and k‐ϵ mixing schemes for a regional domain in the Bay of Bengal (BoB) using the Modular Ocean Model version 5 (MOM5). It is observed that sea surface temperature (SST) and the mixed layer depth (MLD) show significant improvement with the k‐ϵ mixing scheme. Energetic analysis shows that changes in the viscous dissipation and turbulent buoyancy flux are the primary reason for improvement with k‐ϵ. The overestimation of viscous dissipation in the KPP scheme is corrected by k‐ϵ, resulting in a deeper mixed layer closer to observations. The tendency of buoyancy flux to retain stability in the water column also results in a better representation of SST in k‐ϵ. Overall, we conclude that the k‐ϵ mixing scheme works better for the BoB region.

Roles of Atmosphere Thermodynamic and Ocean Dynamic Processes on the Upward Trend of Summer Marine Heatwaves Occurrence in East Asian Marginal Seas

By analyzing the European Centre for Medium-Range Weather Forecasts reanalysis version 5 (ERA5) dataset, we found increased frequency of marine heatwaves (MHWs) in East Asian marginal seas (EAMS) during the boreal summer (June-July-August) in the recent past. To examine which processes are responsible for the upward trend of MHW occurrence, we performed three numerical simulations using Modular Ocean Model version 5 (MOM5) forced by ERA5 dataset. The first experiment used historical atmospheric variables to force the MOM5 for 1982 to 2020, which reasonably simulated the upward trend of MHWs as well as its dominant variability in terms of temporal and spatial structure in EAMS. The second (third) experiment is the same as in the first except that the atmosphere variables used to force the MOM5 consisted of thermodynamic (dynamic) variables only. The upward trend of MHW occurrence in EAMS is simulated in the first and the second experiment only. We argue that the atmosphere thermodynamic processes, in particular, the shortwave radiative forcing, play a key role in inducing the upward trend of MHW occurrence in EAMS during the boreal summer compared to the ocean dynamic processes.

Sensitivity analysis of vertical mixing schemes in a regional domain using modular Ocean model

ABSTRACT In this study, a regional modelling approach is adopted using the Modular Ocean Model version 5 (MOM5) with implementation of open boundary condition (OBC) in the Bay of Bengal (BoB) region. The domain is given an initial stratification profile of climatological temperature and salinity and is forced using seasonally varying wind and air-sea fluxes at the surface. A sensitivity analysis is performed by changing the vertical mixing schemes. Changes in vertical mixing schemes have significant impact on the ocean system, including the surface properties. Two different vertical mixing models are used: K-profile parameterization (KPP), and k- turbulence model. Inter-comparison between these two experiments suggests that k- model performs seemingly better than the KPP model. With k- mixing scheme, the simulated sea surface temperature (SST) and mixed layer depth (MLD) are closer to observations. Model generated turbulent kinetic energy (k) and dissipation () are different in the two experiments because of different representations of k and in the two models. The results show the importance of regional modelling and the use of different mixing schemes. Employing a physics-based vertical mixing scheme, such as the k- turbulence model, shows improvement in the model physics and the model simulated ocean parameters.

A framework to evaluate and elucidate the driving mechanisms of coastal sea surface <i>p</i>CO<sub>2</sub> seasonality using an ocean general circulation model (MOM6-COBALT)

Abstract. The temporal variability of the sea surface partial pressure of CO2 (pCO2) and the underlying processes driving this variability are poorly understood in the coastal ocean. In this study, we tailor an existing method that quantifies the effects of thermal changes, biological activity, ocean circulation and freshwater fluxes to examine seasonal pCO2 changes in highly variable coastal environments. We first use the Modular Ocean Model version 6 (MOM6) and biogeochemical module Carbon Ocean Biogeochemistry And Lower Trophics version 2 (COBALTv2) at a half-degree resolution to simulate coastal CO2 dynamics and evaluate them against pCO2 from the Surface Ocean CO2 Atlas database (SOCAT) and from the continuous coastal pCO2 product generated from SOCAT by a two-step neuronal network interpolation method (coastal Self-Organizing Map Feed-Forward neural Network SOM-FFN, Laruelle et al., 2017). The MOM6-COBALT model reproduces the observed spatiotemporal variability not only in pCO2 but also in sea surface temperature, salinity and nutrients in most coastal environments, except in a few specific regions such as marginal seas. Based on this evaluation, we identify coastal regions of “high” and “medium” agreement between model and coastal SOM-FFN where the drivers of coastal pCO2 seasonal changes can be examined with reasonable confidence. Second, we apply our decomposition method in three contrasted coastal regions: an eastern (US East Coast) and a western (the Californian Current) boundary current and a polar coastal region (the Norwegian Basin). Results show that differences in pCO2 seasonality in the three regions are controlled by the balance between ocean circulation and biological and thermal changes. Circulation controls the pCO2 seasonality in the Californian Current; biological activity controls pCO2 in the Norwegian Basin; and the interplay between biological processes and thermal and circulation changes is key on the US East Coast. The refined approach presented here allows the attribution of pCO2 changes with small residual biases in the coastal ocean, allowing for future work on the mechanisms controlling coastal air–sea CO2 exchanges and how they are likely to be affected by future changes in sea surface temperature, hydrodynamics and biological dynamics.

GFDL's SPEAR Seasonal Prediction System: Initialization and Ocean Tendency Adjustment (OTA) for Coupled Model Predictions

AbstractThe next‐generation seasonal prediction system is built as part of the Seamless System for Prediction and EArth System Research (SPEAR) at the Geophysical Fluid Dynamics Laboratory (GFDL) of the National Oceanic and Atmospheric Administration (NOAA). SPEAR is an effort to develop a seamless system for prediction and research across time scales. The ensemble‐based ocean data assimilation (ODA) system is updated for Modular Ocean Model Version 6 (MOM6), the ocean component of SPEAR. Ocean initial conditions for seasonal predictions, as well as an ocean state estimation, are produced by the MOM6 ODA system in coupled SPEAR models. Initial conditions of the atmosphere, land, and sea ice components for seasonal predictions are constructed through additional nudging experiments in the same coupled SPEAR models. A bias correction scheme called ocean tendency adjustment (OTA) is applied to coupled model seasonal predictions to reduce model drift. OTA applies the climatological temperature and salinity increments obtained from ODA as three‐dimensional tendency terms to the MOM6 ocean component of the coupled SPEAR models. Based on preliminary retrospective seasonal forecasts, we demonstrate that OTA reduces model drift—especially sea surface temperature (SST) forecast drift—in coupled model predictions and improves seasonal prediction skill for applications such as El Niño–Southern Oscillation (ENSO).

Sensitivity of Subsurface Processes of Equatorial Pacific Ocean to the Heat and Momentum Fluxes: A Case Study of 1997-98 El Niño

Ananya, K.; Anant, P.; Chowdary, J.S., and Gnanaseelan, C., 2020. Sensitivity of subsurface processes of equatorial Pacific Ocean to the heat and momentum fluxes: A case study of 1997-98 El Nino. In: Sheela Nair, L.; Prakash, T.N.; Padmalal, D., and Kumar Seelam, J. (eds.), Oceanic and Coastal Processes of the Indian Seas. Journal of Coastal Research, Special Issue No. 89, pp. 26-31. Coconut Creek (Florida), ISSN 0749-0208.The influence of accurate heat and momentum fluxes on 1997-98 El Nino simulation is investigated using Geophysical Fluid Dynamics Laboratory (GFDL) ocean model Modular Ocean Model version 5 (MOM5). Control experiment (CTRL) is carried out by using surface forcing from the CORE2 inter-annual flux, whereas sensitivity experiment (OAERA) is carried out by using heat fluxes from WHOI Objectively analysed air-sea fluxes (OAFlux) data and momentum fluxes from ERA-interim (ERA-I). Both experiments are carried out for a common period of 1985-2009. These experiments revealed that the strength of inter-annual variability is sensitive to accuracy of the forcing. In particular, the sensitivity experiment displayed better simulation of 1997-98 El Nino features such as developing and peak phases. The strength of Nino indices (mainly Nino 3 and Nino 3.4) in OAERA is comparable to EN 4/ORAS 3 more than CTRL. Further analysis reveals that throughout the equatorial Pacific Ocean upper ocean temperature anomaly evolution during the developing to peak phase is improved in OAERA, which is further confirmed by the mixed layer temperature anomaly tendency (TAT) evolution. Detailed analysis of dynamical feedback contribution to TAT indicates that in CTRL, thermocline and zonal advection feedbacks are overestimated and their temporal evolution is inconsistent compared to ORAS 3, whereas these feedbacks are consistent in OAERA, leading to better simulation of Nino indices. Our study concludes that accurate heat flux and momentum flux forcing can improve the simulation of Nino indices and equatorial Pacific upper ocean temperature anomaly associated with the strong El Nino 1997-98.

Impact of excess and deficit river runoff on Bay of Bengal upper ocean characteristics using an ocean general circulation model

The present study investigates the impact of excess river runoff (eRR) and deficit river runoff (dRR) on the Bay of Bengal (BoB) upper ocean physics and circulation patterns using high resolution Modular Ocean Model version 5 (MOM5) simulations. The ocean model MOM5 was forced by 3-hourly surface fluxes and interannual river runoff from the Japanese 55-year Reanalysis (JRA-55). Sensitivity experiments are carried out with interannual and climatological river discharges from 1965 to 2016. Four positive river runoff anomaly years (1980, 1988, 1990, 2007) and four negative river runoff anomaly years (1979, 1986, 1992, 2009) during the satellite era, which are not influenced by the equatorial wind anomalies, are considered for the detailed analysis of eRR and dRR years. The study reveals that the distribution of salinity and the freshwater plume in eRR years differ significantly in the northern and western BoB from that of dRR years. The sea surface salinity difference is ~2 psu in the northern BoB and the advection of freshwater by the southward East India Coastal Current (EICC) reaches the southern part of the BoB and enters the Arabian Sea in the eRR years. A strong cooling is observed in eRR years over the plume distributed area during post-monsoon and the excess freshwater amplifies the EICC as well. The large inflow of freshwater during eRR years is closely associated with a shallow mixed layer depth (MLD), formation of a thick barrier layer (BL), and strong circulation and temperature inversions, while the dRR years accumulate more heat compared to the eRR years in the upper 100 m of the plume area. This study, therefore, provides evidence for the impact of freshwater discharge on the BoB upper ocean processes. These may have a large impact on the local air-sea coupled processes and so representing accurate river discharge in climate models is crucial. It is also found that the EICC and the basin-wide cyclonic gyre advect the barrier layer along the Indian east coast into the southeastern Arabian Sea. This is one of the first studies to incorporate interannual runoff of all the major rivers flowing into the BoB in an ocean general circulation model for investigations of BoB processes.

Toward an Energetically Consistent, Resolution Aware Parameterization of Ocean Mesoscale Eddies

AbstractA subgrid‐scale eddy parameterization is developed, which makes use of an explicit eddy kinetic energy budget and can be applied at both “non‐eddying” and “eddy‐permitting” resolutions. The subgrid‐scale eddies exchange energy with the resolved flow in both directions via a parameterization of baroclinic instability (based on the established formulation of Gent and McWilliams) and biharmonic and negative Laplacian viscosity terms. This formulation represents the turbulent cascades of energy and enstrophy consistent with our current understanding of the turbulent eddy energy cycle. At the same time, the approach is simple and general enough to be readily implemented in ocean climate models, without adding significant computational cost. The closure has been implemented in the Modular Ocean Model Version 6 and tested in the “Neverworld” configuration, which employs an idealized analytically defined topography designed as a testbed for mesoscale eddy parameterizations. The parameterization performs well over a range of resolutions, seamlessly connecting non‐eddying and eddy‐resolving regimes.

Effects of different freshwater flux representations in an ocean general circulation model of the tropical Pacific

Freshwater flux (FWF) is a major forcing that affects the ocean through several processes. The effects of FWF may be represented in ocean modeling as real freshwater flux (RFF) formulations and virtual salt flux (VSF) methods. RFF formulations have been implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Model version 5 (MOM5) as a replacement for the non-physical VSF method, which is primarily used in state-of-the-art ocean models. Here, we systematically evaluated the effects of RFF-related processes on the GFDL MOM5-based simulations in the tropical Pacific. When the FWF was treated as the natural boundary condition (NBC), it directly decreased the local temperature and the salinity by changing the volume of the top model layer, and it increased the temperature in the eastern Pacific by triggering an eastward Goldsbrough–Stommel circulation in the subsurface. Moreover, the heat content induced by the FWF tended to counteract the decreasing effects of the NBC on sea surface temperatures (SSTs) in the western-central tropical Pacific. The relationships between SST perturbations and the FWF representation in ocean modeling are also discussed.

Increased Surface Ocean Heating by Colored Detrital Matter (CDM) Linked to Greater Northern Hemisphere Ice Formation in the GFDL CM2Mc ESM

Abstract Recent observations of Arctic Ocean optical properties have found that colored dissolved organic matter (CDOM) is of primary importance in determining the nonwater absorption coefficient of light in this region. Although CDOM is an important optical constituent in the Arctic Ocean, it is not included in most of the current generation of Earth system models (ESMs). In this study, model runs were conducted with and without light attenuation by colored detrital matter (CDM), the combined optical contribution of CDOM and nonalgal particles. The fully coupled GFDL CM2 with Modular Ocean Model version 4p1 (MOM4p1) at coarse resolution (CM2Mc) ESM was used to examine the differences in heating and ice formation in the high northern latitudes. The annual cycle of sea surface temperature (SST) is amplified in the model run where the optical attenuation by CDM is included. Annually averaged integrated ice mass is 5% greater and total ice extent is 6% greater owing to colder wintertime SSTs. Differences in ocean heating (i.e., temperature tendency) between the two model runs are well represented by the combined changes in heating by penetrating shortwave radiation, mixing, and surface heat fluxes in the upper 100 m. Shortwave radiation is attenuated closer to the surface, which reduces heating below 10 m during summer months. Mixing entrains colder waters into the mixed layer during the autumn and winter months. Increased cloudiness and ice thickness in the model run with CDM reduces incoming shortwave radiation.

Weather noise leading to El Niño diversity in an ocean general circulation model

The frequency of Central Pacific (CP) El Nino occurrences has increased since the late 1990s. In spite of a wealth of studies, however, the physical mechanisms that have caused the change remain unclear. We hypothesize that atmospheric weather noise plays a role in these occurrences. To test this hypothesis, we conduct four simulations using Modular Ocean Model version 4 (MOM4) forced by atmospheric weather noise. In this study, the atmospheric weather noise is defined as the random noise obtained from the European Centre for Medium-Range Weather Forecasts atmospheric datasets. In the first experiment, MOM4 is forced by atmospheric weather noise before 1999 along with the corresponding climatological mean state. In the second experiment, MOM4 is forced by atmospheric weather noise after 1999 along with the corresponding climatological mean state. The third and fourth experiments are similar to the first two experiments except the time periods of the climatological mean state are switched. The results show that atmospheric weather noise may play a more important role than the climatological mean state in the increase of CP El Nino occurrences. This implies that the El Nino diversity could be caused by the modulation of atmospheric weather noise. Therefore, it is important to explore how the atmospheric weather noise might change in light of global warming.

The performance of a z-level ocean model in modeling the global tide

The performance of a z-level ocean model, the Modular Ocean Model Version 4 (MOM4), is evaluated in terms of simulating the global tide with different horizontal resolutions commonly used by climate models. The performance using various sets of model topography is evaluated. The results show that the optimum filter radius can improve the simulated co-tidal phase and that better topography quality can lead to smaller rootmean square (RMS) error in simulated tides. Sensitivity experiments are conducted to test the impact of spatial resolutions. It is shown that the model results are sensitive to horizontal resolutions. The calculated absolute mean errors of the co-tidal phase show that simulations with horizontal resolutions of 0.5° and 0.25° have about 35.5% higher performance compared that with 1° model resolution. An internal tide drag parameterization is adopted to reduce large system errors in the tidal amplitude. The RMS error of the best tuned 0.25° model compared with the satellite-altimetry-constrained model TPXO7.2 is 8.5 cm for M2. The tidal energy fluxes of M2 and K1 are calculated and their patterns are in good agreement with those from the TPXO7.2. The correlation coefficients of the tidal energy fluxes can be used as an important index to evaluate a model skill.

Seasonal precipitation forecast skill over Iran

This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three National Multi-Model Ensemble (NMME) models, and two coupled ocean–atmosphere or one-tiered models. These models are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature (SST) anomalies forecasted using constructed analogue SSTs (ECHAM4.5-SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012 and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 (ECHAM4.5-MOM3-DC2) and the ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST). The precipitation and 850 hPa geopotential height fields of the forecast models are statistically downscaling to the 0.5° × 0.5° spatial resolution of the Global Precipitation Climatology Centre (GPCC) Version 6 gridded precipitation data, using model output statistics (MOS) developed through the canonical correlation analysis (CCA) option of the Climate Predictability Tool (CPT). Retroactive validations for lead times of up to 3 months are performed using the relative operating characteristic (ROC) and reliability diagrams, which are evaluated for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record over the 15-year test period of 1995/1996 to 2009/2010. The forecast models' skills are also compared with skills obtained by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850 hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times of up to 3 months for autumn precipitation – the October-November-December (OND) season. For most seasons, a high skill is obtained from ECHAM4.5-MOM3-DC2 forecasts at a 1-month lead time when the models' 850 hPa geopotential height fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the observed and forecasts over the study area for the OND, November-December-January (NDJ), December-January-February (DJF) and January-February-March (JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectively.

Simulation of the Natural Distribution of Carbon and Nutrients in the Ocean Based on the Global Ocean Carbon Cycle Model MOM4_L40

AbstractA global ocean carbon cycle circulation model which was developed by the National Climate Center, China Meteorological Administration is presented and the basic performance of this model is analyzed and evaluated in this paper. This model is a global three‐dimensional (3D) ocean carbon cycle circulation model, with 40 layers in vertical direction, and biogeochemical processes developed on the basis of the global ocean circulation model MOM4 (Modular Ocean Model version 4) of the US Geophysical Fluid Dynamics Laboratory (GFDL), which is abbreviated as MOM4_L40 (Modular Ocean Model Version 4 with 40 Levels). This model has been integrated for over 1000 years under climate field forcing. The results indicate that, when compared with the observations, this model can more effectively simulate the surface and vertical distribution characteristics of the ocean temperature, salinity, total carbon dioxide, total alkalinity, and total phosphate levels. The simulated distribution of the total CO2 in the ocean is basically consistent with observations, of which a low‐value zone exists on the surface, beneath which is a high‐value zone from 10°S to 60°N. However, the simulations above 2000 m are smaller than observations while simulations below 2000 m are larger than observations. In general, the MOM4_L40 model is found to be a reliable tool for the simulation and research of oceanic carbon cycle processes.

Nonlinear Feedbacks Associated with the Indian Ocean Dipole and Their Response to Global Warming in the GFDL-ESM2M Coupled Climate Model

Abstract A feature of the Indian Ocean dipole (IOD) is its positive skewness, with cold IOD east pole (IODE) sea surface temperature anomalies (SSTAs) exhibiting larger amplitudes than warm SSTAs. Using the coupled Geophysical Fluid Dynamics Laboratory Earth System Model with Modular Ocean Model version 4 (MOM4) component (GFDL-ESM2M), the role of nonlinear feedbacks in generating this positive skewness is investigated and their response to global warming examined. These feedbacks are a nonlinear dynamic heating process, the Bjerknes feedback, wind–evaporation–SST feedback, and SST–cloud–radiation feedback. Nonlinear dynamic heating assists IOD skewness by strongly damping warm IODE SSTAs and reinforcing cold IODE anomalies. In a warmer climate, the damping strengthens while the reinforcement weakens. The SST–thermocline relationship is part of the positive Bjerknes feedback and contributes strongly to IOD skewness as it is weak during the development of warm IODE SSTAs, but strong during the development of cold IODE SSTAs. In response to global warming, this relationship displays weaker asymmetry associated with weaker westerly winds over the central equatorial Indian Ocean. The negative SST–cloud–radiation feedback is also asymmetric with cold IODE SSTAs less damped by incoming shortwave radiation. Under global warming, the damping of cold IODE SSTAs shows little change but warm IODE SSTAs become more damped. This stronger damping is a symptom of negative IODs becoming stronger in amplitude due to the mean IODE thermocline shoaling. The wind–evaporation–SST feedback does not contribute to IOD asymmetry with cold IODE SSTAs decreasing evaporation, which in turn warms the surface. However, as this study focuses on one model, the response of these feedbacks to global warming is uncertain.