ALBERT

Description: Two atmospheric general circulation models (AGCMs), differing in numerics and physical parameterizations, are employed to test the hypothesis that El Niño–induced sea surface temperature (SST) anomalies in the tropical Indian Ocean impact considerably the Northern Hemisphere extratropical circulation anomalies during boreal winter [January–March +1 (JFM +1)] of El Niño years. The hypothesis grew out of recent findings that ocean dynamics influence SST variations over the southwest Indian Ocean (SWIO), and these in turn impact local precipitation. A set of ensemble simulations with the AGCMs was carried out to assess the combined and individual effects of tropical Pacific and Indian Ocean SST anomalies on the extratropical circulation. To elucidate the dynamics responsible for the teleconnection, solutions were sought from a linear version of one of the AGCMs. Both AGCMs demonstrate that the observed precipitation anomalies over the SWIO are determined by local SST anomalies. Analysis of the circulation response shows that over the Pacific–North American (PNA) region, the 500-hPa height anomalies, forced by Indian Ocean SST anomalies, oppose and destructively interfere with those forced by tropical Pacific SST anomalies. The model results validated with reanalysis data show that compared to the runs where only the tropical Pacific SST anomalies are specified, the root-mean-square error of the height anomalies over the PNA region is significantly reduced in runs in which the SST anomalies in the Indian Ocean are prescribed in addition to those in the tropical Pacific. Among the ensemble members, both precipitation anomalies over the SWIO and the 500-hPa height over the PNA region show high potential predictability. The solutions from the linear model indicate that the Rossby wave packets involved in setting up the teleconnection between the SWIO and the PNA region have a propagation path that is quite different from the classical El Niño–PNA linkage. The results of idealized experiments indicate that the Northern Hemisphere extratropical response to Indian Ocean SST anomalies is significant and the effect of this response needs to be considered in understanding the PNA pattern during El Niño years. The results presented herein suggest that the tropical Indian Ocean plays an active role in climate variability and that accurate observation of SST there is of urgent need.

Description: The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses. The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

Description: The present study examines the correspondence between short- and long-term systematic errors in five atmospheric models by comparing the 16 five-day hindcast ensembles from the Transpose Atmospheric Model Intercomparison Project II (Transpose-AMIP II) for July–August 2009 (short term) to the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and AMIP for the June–August mean conditions of the years of 1979–2008 (long term). Because the short-term hindcasts were conducted with identical climate models used in the CMIP5/AMIP simulations, one can diagnose over what time scale systematic errors in these climate simulations develop, thus yielding insights into their origin through a seamless modeling approach. The analysis suggests that most systematic errors of precipitation, clouds, and radiation processes in the long-term climate runs are present by day 5 in ensemble average hindcasts in all models. Errors typically saturate after few days of hindcasts with amplitudes comparable to the climate errors, and the impacts of initial conditions on the simulated ensemble mean errors are relatively small. This robust bias correspondence suggests that these systematic errors across different models likely are initiated by model parameterizations since the atmospheric large-scale states remain close to observations in the first 2–3 days. However, biases associated with model physics can have impacts on the large-scale states by day 5, such as zonal winds, 2-m temperature, and sea level pressure, and the analysis further indicates a good correspondence between short- and long-term biases for these large-scale states. Therefore, improving individual model parameterizations in the hindcast mode could lead to the improvement of most climate models in simulating their climate mean state and potentially their future projections.

Description: The interaction between synoptic eddy and low-frequency flow (SELF) has been recognized for decades to play an important role in the dynamics of the low-frequency variability of the atmospheric circulation. In this three-part study a linear framework with a stochastic basic flow capturing both the climatological mean flow and climatological measures of the synoptic eddy flow is proposed. Based on this linear framework, a set of linear dynamic equations is derived for the ensemble-mean eddy forcing that is generated by anomalous time-mean flows. By assuming that such dynamically determined eddy-forcing anomalies approximately represent the time-mean anomalies of the synoptic eddy forcing and by using a quasi-equilibrium approximation, an analytical nonlocal dynamical closure is obtained for the two-way SELF feedback. This linear closure, directly relating time-mean anomalies of the synoptic eddy forcing to the anomalous time–mean flow, becomes an internal part of a new linear dynamic system for anomalous time–mean flow that is referred to as the low-frequency variability of the atmospheric circulation in this paper. In Part I, the basic approach for the SELF closure is illustrated using a barotropic model. The SELF closure is tested through the comparison of the observed eddy-forcing patterns associated with the leading low-frequency modes with those derived using the SELF feedback closure. Examples are also given to illustrate an important role played by the SELF feedback in regulating the atmospheric responses to remote forcing. Further applications of the closure for understanding the dynamics of low-frequency modes as well as the extension of the closure to a multilevel primitive equation model will be given in Parts II and III, respectively.

Description: Amidst stormy atmospheric circulation, there are prominent recurrent patterns of variability in the planetary circulation, such as the Antarctic Oscillation (AAO), Arctic Oscillation (AO) or North Atlantic Oscillation (NAO), and the Pacific–North America (PNA) pattern. The role of the synoptic eddy and low-frequency flow (SELF) feedback in the formation of these dominant low-frequency modes is investigated in this paper using the linear barotropic model with the SELF feedback proposed in Part I. It is found that the AO-like and AAO-like leading singular modes of the linear dynamical system emerge from the stormy background flow as the result of a positive SELF feedback. This SELF feedback also prefers a PNA-like singular vector as well among other modes under the climatological conditions of northern winters. A model with idealized conditions of basic mean flow and activity of synoptic eddy flow and a prototype model are also used to illustrate that there is a natural scale selection for the AAO- and AO-like modes through the positive SELF feedback. The zonal scale of the localized features in the Atlantic (southern Indian Ocean) for AO (AAO) is largely related to the zonal extent of the enhanced storm track activity in the region. The meridional dipole structures of AO- and AAO-like low-frequency modes are favored because of the scale-selective positive SELF feedback, which can be heuristically understood by the tilted-trough mechanism.

Description: In this three-part study, a linear closure has been developed for the synoptic eddy and low-frequency flow (SELF) interaction and demonstrated that internal dynamics plays an important role in generating the leading low-frequency modes in the extratropical circulation anomalies during cold seasons. In Part III, a new linearized primitive equation system is first derived for time-mean flow anomalies. The dynamical operator of the system includes a traditional part depending on the observed climatological mean state and an additional part from the SELF feedback closure utilizing the observed climatological properties of synoptic eddy activity. The latter part relates nonlocally all the anomalous eddy-forcing terms in equations of momentum, temperature, and surface pressure to the time-mean flow anomalies. Using the observational data, the closure was validated with reasonable success, and it was found that terms of the SELF feedback in the momentum and pressure equations tend to reinforce the low-frequency modes, whereas those in the thermodynamic equation tends to damp the temperature anomalies to make the leading modes equivalent barotropic. Through singular vector analysis of the linear dynamical operator, it is highlighted that the leading modes of the system resemble the observed patterns of the Arctic Oscillation, Antarctic Oscillation, and Pacific–North American pattern, in which the SELF feedback plays an essential role, consistent with the finding of the barotropic model study in Part II.