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Ben P. Kirtman

Abstract

Results are described from a large sample of coupled ocean–atmosphere retrospective forecasts during 1980–99. The prediction system includes a global anomaly coupled general circulation model and a state-of-the-art ocean data assimilation system. The retrospective forecasts are initialized each January, April, July, and October of each year, and ensembles of six forecasts are run for each initial month, yielding a total of 480 1-yr predictions.

In generating the ensemble members, perturbations are added to the atmospheric initial state only. The skill of the prediction system is analyzed from both a deterministic and a probabilistic perspective. The probabilistic approach is used to quantify the uncertainty in any given forecast. The deterministic measures of skill for eastern tropical Pacific SST anomalies (SSTAs) suggest that the ensemble mean forecasts are useful up to lead times of 7–9 months. At somewhat shorter leads, the forecasts capture some aspects of the variability in the tropical Indian and Atlantic Oceans. The ensemble mean precipitation anomaly has disappointingly low correlation with observed rainfall. The probabilistic measures of skill (relative operating characteristics) indicate that the distribution of the ensemble provides useful forecast information that could not easily be gleaned from the ensemble mean. In particular, the prediction system has more skill at forecasting cold ENSO events compared to warm events. Despite the fact that the ensemble mean rainfall is not well correlated with the observed, the ensemble distribution does indicate significant regions where there is useful information in the forecast ensemble. In fact, it is possible to detect that droughts over land are more predictable than floods. It is argued that probabilistic verification is an important complement to any deterministic verification, and provides a useful and quantitative way to measure uncertainty.

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Ben P. Kirtman

Abstract

Tropical ocean wave dynamics associated with the El Niño–Southern Oscillation cycle in a coupled model are examined. The ocean–atmosphere model consists of statistical atmosphere coupled to a simple reduced gravity model of the tropical Pacific Ocean. The statistical atmosphere is simple enough to allow for the structure and position of the wind stress anomalies to be externally specified. In a control simulation, where the structure of the wind stress anomaly is determined from observations, the model produces a regular 5-yr oscillation. This simulation is consistent with the so-called delayed oscillator theory in that subsurface wave dynamics determine the slow timescale of the oscillation and surface-layer processes are found to be of secondary importance. Kelvin and Rossby wave propagation is detected along the equator, with periods considerably shorter than the simulated oscillation period. The way in which these relatively fast waves are related to the simulated 5-yr oscillation is discussed.

In order to understand the mechanism responsible for the 5-yr period in the control simulation, two sets of sensitivity experiments were conducted. The first set of experiments focused on how the meridional structure of the wind stress anomaly influences the model ENSO period. Relatively broad (narrow) meridional structures lead to relatively long (short) periods. While the gravest Rossby wave appears to be important in these simulations, it is found that the maximum variability in the thermocline is associated with off-equatorial Rossby waves (i.e., Rossby waves that have a maximum amplitude beyond ±7° of the equator). The second set of sensitivity experiments was designed to examine how these off-equatorial Rossby waves influence the ENSO cycle. Without the effects of the off-equatorial Rossby waves at the western boundary, the model produces a 2-yr oscillation regardless of the meridional structure of the wind stress anomaly. The mechanism by which these off-equatorial Rossby waves influence the ENSO period is described. Based on these experiments, it is shown that the reflection of the gravest Rossby wave off the western boundary is required to produce oscillatory behavior in the model, but the period of the oscillation is determined by the off-equatorial Rossby waves and the latitude at which they are forced.

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Ben P. Kirtman
and
Stephen E. Zebiak

Abstract

A hybrid coupled model (HCM) consisting of a tropical Pacific Ocean and global atmosphere is presented. The ocean component is a linear reduced gravity model of the upper ocean in the tropical Pacific. The atmospheric component is a triangular 30 horizontal resolution global spectral general circulation model with 18 unevenly spaced levels in the vertical. In coupling these component models, an anomaly coupling strategy is employed. A 40-yr simulation was made with HCM and the variability in the tropical Pacific was compared to the observed variability. The HCM produces irregular ENSO events with a broad spectrum of periods between 12 and 48 months. On longer timescales, approximately 48 months, the simulated variability was weaker than the observed and on shorter timescales (approximately 24 months) the simulated variability was too strong. The simulated variability is asymmetric in the sense that the amplitude of the warm events is realistic, but there are no significant cold events.

An ensemble of 60 hindcast predictions was made with the HCM and the skill was compared to other prediction systems. In forecasting sea surface temperature anomalies in the eastern Pacific, the HCM is comparable to the other prediction systems for lead times up to 10 months. The anomaly correlation coefficient for the eastern Pacific SSTA remains above 0.6 for lead times of up to 11 months. Consistent with the 40-yr simulation, hindcasts of cold events have little skill, particularly when compared to hindcasts of warm events. Specific hindcasts also demonstrate that the HCM also has difficulty predicting the transition from warm conditions to normal or cold conditions.

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Ben P. Kirtman
and
David G. DeWitt

Abstract

The Geophysical Fluid Dynamics Laboratory ocean model has been used to diagnose the sensitivity of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model wind stress to convective parameterization. In a previous study this atmospheric model was integrated for seven years with observed sea surface temperatures to test three different convective parameterizations: Kuo, Betts–Miller, and relaxed Arakawa–Schubert. In this study, the three wind stress fields are then used to force the ocean model. For comparison, an ocean model simulation with the subjectively analyzed Florida State University wind stress product is also made. The resulting ocean temperature field is compared with the National Centers for Environmental Prediction ocean analyses in terms of the annual cycle and interannual variability in order to identify errors in the ocean model and errors that are unique to the particular wind stress field. Overall, the ocean simulation with the wind stress resulting from the relaxed Arakawa–Schubert parameterization gives a thermal structure that is in best agreement with the analyzed wind stress simulation and the ocean analyses.

Based on the simulation of the annual cycle of sea surface temperature and heat content in the deep Tropics, it is concluded that the wind stress is too strong with the Betts–Miller parameterization and too weak with the Kuo parameterization, particularly in the boreal spring. The simulation with the wind stress from the relaxed Arakawa–Schubert parameterization minimizes the errors in the heat content between 10°S and 10°N and has smaller errors than the analyzed wind stress simulation in some regions. In terms of interannual variability, the anomalies from all three wind stress products produce sea surface temperature anomalies that are concentrated in the western Pacific with little or no sea surface temperature anomaly in the east indicating that the ocean model has some difficulty capturing the remote response to anomalous wind stress forcing. However, the subsurface temperature anomalies along the equator are best simulated with the wind stress from the relaxed Arakawa–Schubert parameterization.

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Ben P. Kirtman
and
Dughong Min

Abstract

Results are described from a large sample of coupled ocean–atmosphere retrospective forecasts during 1982–98. The prediction system is based on the National Center for Atmospheric Research (NCAR) Community Climate System Model, version 3 (CCSM3.0), and a state-of-the-art ocean data assimilation system made available by the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL). The retrospective forecasts are initialized in January, April, July, and November of each year, and ensembles of 6 forecasts are run for each initial month, yielding a total of 408 1-yr predictions. In generating the ensemble members, perturbations are added to the atmospheric initial state only. The skill of the prediction system is analyzed from both a deterministic and a probabilistic perspective, it is then compared to the operational NOAA Climate Forecast System (CFS), and the forecasts are combined with CFS to produce a multimodel prediction system. While the skill scores for each model are highly dependent on lead time and initialization month, the overall level of skill of the individual models is quite comparable. The multimodel combination (i.e., the unweighted average of the forecast), while not always the most skillful, is generally as skillful as the best model, using either deterministic or probabilistic skill metrics.

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Rameshan Kallummal
and
Ben P. Kirtman

Abstract

Calculations of the optimal perturbations of an anomaly coupled ocean–atmosphere general circulation model (ACGCM) have been performed using a set of linear (Markov) models best fit to 300 years of continuous simulations. This study aims (i) to verify some of the findings regarding optimals from earlier studies based on relatively less complex coupled models and (ii) to assess how well a linear stochastic model reproduces the interannual variability of the tropical Pacific in the ACGCM.

The Markov models are built in a multivariate (i.e., sea surface temperature, heat content, zonal and meridional components of wind stress, and total heat flux) empirical orthogonal function (MEOF) space with reduced dimension while retaining the important covariability. These empirical models are trained in the first 300 yr and verified in the last 50 yr of the data. The Markov model with eight retained MEOFs (MK8) shows, in terms of the anomaly correlations, the best predictive skill of interannual variability in the ACGCM for up to about a year.

The main conclusions of this study are as follows:

(i) The singular values of MK8 show a strong seasonal dependence, indicating seasonal variation in the Markov models, which in turn implies the importance of seasonality in the internal dynamics. From the perspective of a stochastic model, this may also indicate that neither the nonlinearity in the system nor the seasonality in the stochastic forcing is necessary for the phase locking of the model ENSO to the annual cycle.

(ii) In the tropical Pacific, a narrow region straddling the equator is conducive for the transient growth of perturbations, independent of the season; however, a migration of the maximum growth region from the central to the eastern Pacific from spring to summer to winter is also observed. The western warm pool region is capable of generating transient growth throughout the year. However, the amplitude of the optimal shows some modulation with the annual cycle. Another region where considerable transient growth can occur is the northern subtropics. Therefore, the optimals in this study encompass the features of a coupled model with a statistical atmosphere as well as the features of the coupled model with a dynamical atmosphere in which deep convective parameterization is included.

(iii) In general, the geographical locations of the optimals do not depend on whether EOF analysis is performed on a covariance matrix or on a correlation matrix. Nevertheless, their spatial extent is larger when the correlation matrix is used.

(iv) The spatial distribution of the ratio of local amplitudes of the residual (misfit of the linear models) to the respective local anomaly points to the fact that, in general, a narrow region between 5°S and 5°N in the Pacific Ocean is in a linear regime. However, in the off-equatorial region this linear approximation generally fails. In the equatorial western Pacific west of 160°E, a region where abundant convective activity occurs both in the model and in nature, nonlinear dynamics is important. Therefore, this analysis hints at the possibility of accommodating the two competing points of views of ENSO into a single framework, by virtue of the fact that both linear and nonlinear dynamics seems to operate in a nonoverlapping manner in both space and time.

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Ben P. Kirtman
and
Edwin K. Schneider

Abstract

A series of idealized atmospheric general circulation model (AGCM) experiments are presented. These experiments examine whether and how atmospheric deep moist convection, in the absence of meridional gradients in external forcing, interacts with the large-scale flow, becoming spatially organized and yielding a coherent general circulation. In a control simulation, where the SST and the incident solar flux are prescribed to be independent of latitude, longitude, and time, a well-defined intertropical convergence zone (ITCZ) forms. This result suggests that the interaction between convection and the rotation of the earth causes convection and a corresponding general circulation to organize. The actual latitude that the ITCZ forms at, however, may be parameterization dependent. In this control simulation, the SST is not interactive and cannot respond to the spatial variations of the heat flux into the ocean that result from the organization of the circulation. In order to examine the circulation that arises without horizontal gradients in the forcing in a physically consistent, energetically closed, model, the AGCM is coupled to a mixed layer ocean model. In this case, the ITCZ still forms at the equator even though a “reversed” pole-to-equator surface temperature gradient develops.

The SST distribution and the tropospheric circulation are very different between these two experiments, but the surface zonal mean zonal wind is quite similar. In the Tropics, the surface zonal wind is easterly and in the subtropics it is westerly, implying a net poleward transport of angular momentum in both simulations. Large-scale zonally asymmetric convective “events” apparently produce this momentum transport by the barotropic tilted trough mechanism. The role of three-dimensional zonally asymmetric motions in the momentum transport mechanism is tested in another experiment, where the AGCM is truncated to be zonally symmetric. In this case, the model enters a limit cycle where the ITCZ transits between 20°N and 20°S with a 22-month period. The motions associated with this oscillatory behavior accomplish the same poleward transport of angular momentum that the convective events produced in the zonally asymmetric model, but by a drastically different mechanism, suggesting that there may be some undiscovered general principle governing the momentum transport.

Finally, a simple argument is used to estimate the minimum modification to the uniform specified SST necessary to displace the ITCZ off the equator. A last experiment verifies this argument.

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Sang-Wook Yeh
and
Ben P. Kirtman

Abstract

The low-frequency relationship between interannual tropical and North Pacific sea surface temperature anomalies (SSTAs) in observations and a coupled general circulation model (CGCM) is investigated. The authors use the interactive ensemble CGCM, which advances a new approach for artificially increasing the signal-to-noise ratio, making it easier to detect physical and dynamical links with much reduced interference by atmospheric noise. The results presented here suggest that decadal variations in the relationship between the dominant modes of tropical and North Pacific interannual SSTA variability result from changes of spatial manifestation of North Pacific SSTA, both in the observation and in the model.

The authors conjecture that the details of tropical Pacific SST forcing ultimately determine the tropical–North Pacific SST teleconnections, and this conjecture is examined in a much longer time series from a CGCM simulation. There are two patterns of North Pacific interannual SSTA variability in the model. The first pattern is locally forced by noise in the surface air–sea fluxes associated due to internal atmospheric dynamics. The second pattern is remotely forced by tropical SSTA. As the relationship of tropical–North Pacific SST teleconnections varies in the model, the spatial manifestation of the North Pacific SSTA changes from the atmospheric noise-forced pattern to the remotely forced pattern and vice versa. In the model, the amplitude of the tropical Pacific SSTA variance varies on decadal time scales and this largely determines the dominant structure of North Pacific SSTA variability. Furthermore, the change in location of the maximum tropical SST forcing is associated with the changes in the spatial manifestation of North Pacific interannual SSTA variability.

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Cristiana Stan
and
Ben P. Kirtman

Abstract

The influence of atmospheric stochastic forcing and uncertainty in initial conditions on the limit of predictability of the NCEP Climate Forecast System (CFS) is quantified based on comparisons of idealized identical twin prediction experiments using two different coupling strategies. In the first method, called the interactive ensemble, a single oceanic general circulation model (GCM; the Modular Ocean Model version 3 of GFDL) is coupled to the ensemble average of multiple realizations (in this case six ensemble members) of an atmospheric GCM (NCEP Global Forecast System). In the second method the standard CFS is used. The interactive ensemble is specifically designed to reduce the internal atmospheric dynamic fluctuations that are unrelated to the sea surface temperature anomalies via ensemble averaging at the air–sea interface, whereas in the standard CFS, the atmospheric noise (i.e., stochastic forcing) plays an active role in the evolution of the coupled system. In the identical twin experiments presented here, the perfect model approach is taken, thereby explicitly excluding the impact of model error on the estimate of the limit of predictability. The experimental design and the analysis separately consider how uncertainty in the ocean initial conditions (i.e., initial condition noise) versus uncertainty as the forecast evolves (i.e., noise due to internal dynamics of the atmosphere) impact estimates of the limit of predictability. Estimates of the limit of predictability are based on both deterministic measures (ensemble spread and root-mean-square error) and probabilistic measures (relative operating characteristics). The analysis examines both oceanic and atmospheric variables in the tropical Pacific. The overarching result is that noise in the initial condition is the primary factor limiting predictability, whereas noise as the forecast evolves is of secondary importance.

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Renguang Wu
and
Ben P. Kirtman

Abstract

The processes for the coupled tropospheric biennial oscillation involving the Indian monsoon and El Niño–Southern Oscillation (ENSO) are studied through composites of sequential wet monsoon/La Niña year followed by dry monsoon/El Niño year using observations and outputs from the Center for Ocean–Land–Atmosphere Studies (COLA) interactive ensemble coupled general circulation model. The previous composites emphasize the role of ENSO in the monsoon transition but do not exclude the possible role of factors other than ENSO.

It is found that the central eastern equatorial Pacific sea surface temperature (SST) anomalies can affect the Indian monsoon transition by two processes: (i) a shift of large-scale east–west circulation across the equatorial Indian–Pacific Oceans; and (ii) a Rossby wave–type response over the eastern north Indian Ocean–western North Pacific. The former provides the low-level anomalous moisture convergence (divergence) that preconditions the atmosphere for a wet (dry) Indian monsoon. The latter induces anomalous downward (upward) motion and low-level anomalous anticyclonic (cyclonic) circulation over the eastern north Indian Ocean–South China Sea. Associated shortwave radiation and surface evaporation changes favor the eastward shift of cold (warm) SST anomalies and in turn low-level easterly (westerly) anomalies through SST gradient changes.

The moistening (drying) of the atmosphere before a wet (dry) Indian monsoon is due to the low-level anomalous moisture convergence (divergence) that is dominated by anomalous wind convergence of the mean humidity. A large increase (decrease) in surface evaporation is observed in conjunction with the transition to a wet (dry) monsoon. The Indian Ocean SST change is mainly a response to the monsoon and ENSO-induced surface heat flux changes. The Asian land surface condition anomalies are not necessary in this coupled biennial variability of the monsoon–ENSO system in the model.

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