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John Derber and Anthony Rosati

Abstract

A global oceanic four-dimensional data assimilation system has been developed for use in initializing coupled ocean–atmosphere general circulation models and many other applications. The data assimilation system uses a high resolution global ocean model to extrapolate the information forward in time. The data inserted into the model currently consists only of conventional sea surface temperature observations and vertical temperature profiles. The data are inserted continuously into the model by updating the model's temperature solution every timestep. This update is created using a statistical interpolation routine applied to all data in a 30-day window centered on the present timestep.

Large scale features in the sea surface temperature analyses are consistent with those from independent analyses. Subsurface fields created from the assimilation are much more realistic than those produced without the insertion of data. Furthermore, information contained in the assimilation field is shown to be retained in the model solution after the assimilation procedure is terminated. The results are encouraging but further improvements can be made.

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Dujuan Kang, Enrique N. Curchitser, and Anthony Rosati

Abstract

The seasonal variability of the mean kinetic energy (MKE) and eddy kinetic energy (EKE) of the Gulf Stream (GS) is examined using high-resolution regional ocean model simulations. A set of three numerical experiments with different surface wind and buoyancy forcing is analyzed to investigate the mechanisms governing the seasonal cycle of upper ocean energetics. In the GS along-coast region, MKE has a significant seasonal cycle that peaks in summer, while EKE has two comparable peaks in May and September near the surface; the May peak decays rapidly with depth. In the off-coast region, MKE has a weak seasonal cycle that peaks in summer, while EKE has a dominant peak in May and a secondary peak in September near the surface. The May peak also decays with depth leaving the September peak as the only seasonal signal below 100 m. An analysis of the three numerical experiments suggests that the seasonal variability in the local wind forcing significantly impacts the September peak of the along-coast EKE through a local-flow barotropic instability process. Alternatively, the seasonal buoyancy forcing primarily impacts the flow baroclinic instability and is consequently related to the May peak of the upper ocean EKE in both regions. The analysis results indicate that the seasonal cycle of the along-coast MKE is influenced by both local energy generation by wind and the advection of energy from upstream regions. Finally, the MKE cycle and the September peak of EKE in the off-coast region are mainly affected by advection of energy from remote regions, giving rise to correlations with the seasonal cycle of remote winds.

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Richard G. Gudgel, Anthony Rosati, and C. T. Gordon

Abstract

The sensitivity of a coupled general circulation model (CGCM) to tropical marine stratocumulus (MSc) clouds and low-level clouds over the tropical land is examined. The hypothesis that low-level clouds play an important role in determining the strength and position of the Walker circulation and also on the strength and phase of the El Niño–Southern Oscillation (ENSO) is studied using a Geophysical Fluid Dynamics Laboratory (GFDL) experimental prediction CGCM. In the Tropics, a GFDL experimental prediction CGCM exhibits a strong bias in the western Pacific where an eastward shift in the ascending branch of the Walker circulation diminishes the strength and expanse of the sea surface temperature (SST) warm pool, thereby reducing the east–west SST gradient, and effectively weakening the trade winds. These model features are evidence of a poorly simulated Walker circulation, one that mirrors a “perpetual El Niño” state. One possible factor contributing to this bias is a poor simulation of MSc clouds in the eastern equatorial Pacific (which are essential to a proper SST annual cycle). Another possible contributing factor might be radiative heating biases over the land in the Tropics, which could, in turn, have a significant impact on the preferred locations of maximum convection in the Tropics. As a means of studying the sensitivity of a CGCM to both MSc clouds and to varied radiative forcing over the land in the Tropics, low-level clouds obtained from the International Satellite Cloud Climatology Project (ISCCP) are prescribed. The experiment sets consist of one where clouds are fully predicted, another where ISCCP low-level clouds are prescribed over the oceans alone, and a third where ISCCP low-level clouds are prescribed both over the global oceans and over the tropical landmasses. A set of ten 12-month hindcasts is performed for each experiment.

The results show that the combined prescription of interannually varying global ocean and climatological tropical land low-level clouds into the CGCM results in a much improved simulation of the Walker circulation over the Pacific Ocean. The improvement to the tropical circulation was also notable over the Indian and Atlantic basins as well. These improvements in circulation led to a considerable increase in ENSO hindcast skill in the first year by the CGCM. These enhancements were a function of both the presence of MSc clouds over the tropical oceans and were also due to the more realistic positioning of the regions of maximum convection in the Tropics. This latter model feature was essentially a response to the change in radiative forcing over tropical landmasses associated with a reduction in low cloud fraction and optical depth when ISCCP low-level clouds were prescribed there. These results not only underscore the importance of a reasonable representation of MSc clouds but also point out the considerable impact that radiative forcing over the tropical landmasses has on the simulated position of the Walker circulation and also on ENSO forecasting.

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Qian Song, Gabriel A. Vecchi, and Anthony J. Rosati

Abstract

The impacts of the Indonesian Throughflow (ITF) on the tropical Indo–Pacific climate, particularly on the character of interannual variability, are explored using a coupled general circulation model (CGCM). A pair of CGCM experiments—a control experiment with an open ITF and a perturbation experiment in which the ITF is artificially closed—is integrated for 200 model years, with the 1990 values of trace gases. The closure of the ITF results in changes to the mean oceanic and atmospheric conditions throughout the tropical Indo–Pacific domain as follows: surface temperatures in the eastern tropical Pacific (Indian) Ocean warm (cool), the near-equatorial Pacific (Indian) thermocline flattens (shoals), Indo–Pacific warm-pool precipitation shifts eastward, and there are relaxed trade winds over the tropical Pacific and anomalous surface easterlies over the equatorial Indian Ocean. The character of the oceanic changes is similar to that described by ocean-only model experiments, though the amplitude of many features in the tropical Indo–Pacific is amplified in the CGCM experiments.

In addition to the mean-state changes, the character of tropical Indo–Pacific interannual variability is substantially modified. Interannual variability in the equatorial Pacific and the eastern tropical Indian Ocean is substantially intensified by the closure of the ITF. In addition to becoming more energetic, El Niño–Southern Oscillation (ENSO) exhibits a shorter time scale of variability and becomes more skewed toward its warm phase (stronger and more frequent warm events). The structure of warm ENSO events changes; the anomalies of sea surface temperature (SST), precipitation, and surface westerly winds are shifted to the east and the meridional extent of surface westerly anomalies is larger.

In the eastern tropical Indian Ocean, the interannual SST variability off the coast of Java–Sumatra is noticeably amplified by the occurrence of much stronger cooling events. Closing the ITF shoals the eastern tropical Indian Ocean thermocline, which results in stronger cooling events through enhanced atmosphere–thermocline coupled feedbacks. Changes to the interannual variability caused by the ITF closure rectify into mean-state changes in tropical Indo–Pacific conditions. The modified Indo–Pacific interannual variability projects onto the mean-state differences between the ITF open and closed scenarios, rectifying into mean-state differences. These results suggest that CGCMs need to reasonably simulate the ITF in order to successfully represent not just the mean climate, but its variations as well.

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Eli Galanti, Eli Tziperman, Matthew Harrison, Anthony Rosati, and Ziv Sirkes

Abstract

An experimental ENSO prediction system is presented, based on an ocean general circulation model (GCM) coupled to a statistical atmosphere and the adjoint method of 4D variational data assimilation. The adjoint method is used to initialize the coupled model, and predictions are performed for the period 1980–99. The coupled model is also initialized using two simpler assimilation techniques: forcing the ocean model with observed sea surface temperature and surface fluxes, and a 3D variational data assimilation (3DVAR) method, similar to that used by the National Centers for Environmental Prediction (NCEP) for operational ENSO prediction. The prediction skill of the coupled model initialized by the three assimilation methods is then analyzed and compared. The effect of the assimilation period used in the adjoint method is studied by using 3-, 6-, and 9-month assimilation periods. Finally, the possibility of assimilating only the anomalies with respect to observed climatology in order to circumvent systematic model biases is examined.

It is found that the adjoint method does seem to have the potential for improving over simpler assimilation schemes. The improved skill is mainly at prediction intervals of more than 6 months, where the coupled model dynamics start to influence the model solution. At shorter prediction time intervals, the initialization using the forced ocean model or the 3DVAR may result in a better prediction skill. The assimilation of anomalies did not have a substantial effect on the prediction skill of the coupled model. This seems to indicate that in this model the climatology bias, which is compensated for by the anomaly assimilation, is less significant for the predictive skill than the bias in the model variability, which cannot be eliminated using the anomaly assimilation. Changing the optimization period from 6 to 3 to 9 months showed that the period of 6 months seems to be a near-optimal choice for this model.

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Qian Song, Gabriel A. Vecchi, and Anthony J. Rosati

Abstract

The interannual variability of the Indian Ocean, with particular focus on the Indian Ocean dipole/zonal mode (IODZM), is investigated in a 250-yr simulation of the GFDL coupled global general circulation model (CGCM). The CGCM successfully reproduces many fundamental characteristics of the climate system of the Indian Ocean. The character of the IODZM is explored, as are relationships between positive IODZM and El Niño events, through a composite analysis. The IODZM events in the CGCM grow through feedbacks between heat-content anomalies and SST-related atmospheric anomalies, particularly in the eastern tropical Indian Ocean. The composite IODZM events that co-occur with El Niño have stronger anomalies and a sharper east–west SSTA contrast than those that occur without El Niño. IODZM events, whether or not they occur with El Niño, are preceded by distinctive Indo-Pacific warm pool anomaly patterns in boreal spring: in the central Indian Ocean easterly surface winds, and in the western equatorial Pacific an eastward shift of deep convection, westerly surface winds, and warm sea surface temperature. However, delayed onsets of the anomaly patterns (e.g., boreal summer) are often not followed by IODZM events. The same anomaly patterns often precede El Niño, suggesting that the warm pool conditions favorable for both IODZM and El Niño are similar. Given that IODZM events can occur without El Niño, it is proposed that the observed IODZM–El Niño relation arises because the IODZM and El Niño are both large-scale phenomena in which variations of the Indo-Pacific warm pool deep convection plays a central role. Yet each phenomenon has its own dynamics and life cycle, allowing each to develop without the other.

The CGCM integration also shows substantial decadal modulation of the occurrence of IODZM events, which is found to be not in phase with that of El Niño events. There is a weak, though significant, negative correlation between the two. Moreover, the statistical relationship between the IODZM and El Niño displays strong decadal variability.

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Shan Li, Shaoqing Zhang, Zhengyu Liu, Xiaosong Yang, Anthony Rosati, Jean-Christophe Golaz, and Ming Zhao

Abstract

Uncertainty in cumulus convection parameterization is one of the most important causes of model climate drift through interactions between large-scale background and local convection that use empirically set parameters. Without addressing the large-scale feedback, the calibrated parameter values within a convection scheme are usually not optimal for a climate model. This study first designs a multiple-column atmospheric model that includes large-scale feedbacks for cumulus convection and then explores the role of large-scale feedbacks in cumulus convection parameter estimation using an ensemble filter. The performance of convection parameter estimation with or without the presence of large-scale feedback is examined. It is found that including large-scale feedbacks in cumulus convection parameter estimation can significantly improve the estimation quality. This is because large-scale feedbacks help transform local convection uncertainties into global climate sensitivities, and including these feedbacks enhances the statistical representation of the relationship between parameters and state variables. The results of this study provide insights for further understanding of climate drift induced from imperfect cumulus convection parameterization, which may help improve climate modeling.

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Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, Anthony Rosati, Thomas L. Delworth, and Yun Liu

Abstract

Because of the geographic dependence of model sensitivities and observing systems, allowing optimized parameter values to vary geographically may significantly enhance the signal in parameter estimation. Using an intermediate atmosphere–ocean–land coupled model, the impact of geographic dependence of model sensitivities on parameter optimization is explored within a twin-experiment framework. The coupled model consists of a 1-layer global barotropic atmosphere model, a 1.5-layer baroclinic ocean including a slab mixed layer with simulated upwelling by a streamfunction equation, and a simple land model. The assimilation model is biased by erroneously setting the values of all model parameters. The four most sensitive parameters identified by sensitivity studies are used to perform traditional single-value parameter estimation and new geographic-dependent parameter optimization. Results show that the new parameter optimization significantly improves the quality of state estimates compared to the traditional scheme, with reductions of root-mean-square errors as 41%, 23%, 62%, and 59% for the atmospheric streamfunction, the oceanic streamfunction, sea surface temperature, and land surface temperature, respectively. Consistently, the new parameter optimization greatly improves the model predictability as a result of the improvement of initial conditions and the enhancement of observational signals in optimized parameters. These results suggest that the proposed geographic-dependent parameter optimization scheme may provide a new perspective when a coupled general circulation model is used for climate estimation and prediction.

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Colm Sweeney, Anand Gnanadesikan, Stephen M. Griffies, Matthew J. Harrison, Anthony J. Rosati, and Bonita L. Samuels

Abstract

The impact of changes in shortwave radiation penetration depth on the global ocean circulation and heat transport is studied using the GFDL Modular Ocean Model (MOM4) with two independent parameterizations that use ocean color to estimate the penetration depth of shortwave radiation. Ten to eighteen percent increases in the depth of 1% downwelling surface irradiance levels results in an increase in mixed layer depths of 3–20 m in the subtropical and tropical regions with no change at higher latitudes. While 1D models have predicted that sea surface temperatures at the equator would decrease with deeper penetration of solar irradiance, this study shows a warming, resulting in a 10% decrease in the required restoring heat flux needed to maintain climatological sea surface temperatures in the eastern equatorial Atlantic and Pacific Oceans. The decrease in the restoring heat flux is attributed to a slowdown in heat transport (5%) from the Tropics and an increase in the temperature of submixed layer waters being transported into the equatorial regions. Calculations were made using a simple relationship between mixed layer depth and meridional mass transport. When compared with model diagnostics, these calculations suggest that the slowdown in heat transport is primarily due to off-equatorial increases in mixed layer depths. At higher latitudes (5°–40°), higher restoring heat fluxes are needed to maintain sea surface temperatures because of deeper mixed layers and an increase in storage of heat below the mixed layer. This study offers a way to evaluate the changes in irradiance penetration depths in coupled ocean–atmosphere GCMs and the potential effect that large-scale changes in chlorophyll a concentrations will have on ocean circulation.

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Andrew T. Wittenberg, Anthony Rosati, Thomas L. Delworth, Gabriel A. Vecchi, and Fanrong Zeng

Abstract

Observations and climate simulations exhibit epochs of extreme El Niño–Southern Oscillation (ENSO) behavior that can persist for decades. Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations, but they have also shown that interdecadal modulation of ENSO can arise even without such forcings. The present study examines the predictability of this intrinsically generated component of ENSO modulation, using a 4000-yr unforced control run from a global coupled GCM [GFDL Climate Model, version 2.1 (CM2.1)] with a fairly realistic representation of ENSO. Extreme ENSO epochs from the unforced simulation are reforecast using the same (“perfect”) model but slightly perturbed initial conditions. These 40-member reforecast ensembles display potential predictability of the ENSO trajectory, extending up to several years ahead. However, no decadal-scale predictability of ENSO behavior is found. This indicates that multidecadal epochs of extreme ENSO behavior can arise not only intrinsically but also delicately and entirely at random. Previous work had shown that CM2.1 generates strong, reasonably realistic, decadally predictable high-latitude climate signals, as well as tropical and extratropical decadal signals that interact with ENSO. However, those slow variations appear not to lend significant decadal predictability to this model’s ENSO behavior, at least in the absence of external forcings. While the potential implications of these results are sobering for decadal predictability, they also offer an expedited approach to model evaluation and development, in which large ensembles of short runs are executed in parallel, to quickly and robustly evaluate simulations of ENSO. Further implications are discussed for decadal prediction, attribution of past and future ENSO variations, and societal vulnerability.

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