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The present study focuses on the mechanism that controls the transition of the Euro-Atlantic circulation responses to El Niño–Southern Oscillation (ENSO) from early (December) to late winter (February) for the period 1981–2015. A positive phase of ENSO induces a precipitation dipole with increased precipitation in the western and reduced precipitation in the eastern tropical Indian Ocean; this occurs mainly during early winter (December) and less so in late winter (February). It is shown that these interbasin atmospheric teleconnections dominate the response in the Euro-Atlantic sector in early winter by modifying the subtropical South Asian jet (SAJET) and forcing a wavenumber-3 response that projects spatially onto the positive North Atlantic Oscillation (NAO) pattern. On the contrary, during late winter, the response in the Euro-Atlantic sector is dominated by the well-known ENSO wave train from the tropical Pacific region, involving extratropical anomalies that project spatially on the positive phase of the Pacific–North American (PNA) pattern and the negative phase of the NAO pattern. Numerical experiments with an atmospheric model (an AGCM) forced by an Indian Ocean heating dipole anomaly support the hypothesis that the Indian Ocean modulates the SAJET and enforces the Rossby wave propagation to the Euro-Atlantic region in early winter. These phenomena are also investigated using the ECMWF SEAS5 reforecast dataset. In SEAS5, the ENSO interbasin tropical teleconnections and the response of the Euro-Atlantic circulation anomalies and their change from early to late winter are realistically predicted, although the strength of the early winter signal originated from the Indian Ocean is underestimated.

This study uses initialized forecasts and climate integrations to evaluate the wintertime North Atlantic response to an increase of ocean model resolution from ~100 km [low-resolution ocean (LRO)] to ~25 km [high-resolution ocean (HRO)] in the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). Importantly, the simulated impacts are time-scale dependent such that impacts in subseasonal and seasonal forecasts cannot be extrapolated to climate time scales. In general, mean biases are reduced in HRO relative to LRO configurations and the impact is increased at longer lead times. At subseasonal to seasonal lead times, surface heating anomalies over the Gulf Stream are associated with local increases to the poleward heat flux associated with transient atmospheric eddies. In contrast, surface heating anomalies in climate experiments are balanced by changes to the time-mean surface winds that resemble the steady response under linear dynamics. Some aspects of air–sea interaction exhibit a clear improvement with increased resolution at all lead times. However, it is difficult to identify the impact of increased ocean eddy activity in the variability of the overlying atmosphere. In particular, atmospheric blocking and the intensity of the storm track respond more strongly to mean biases and thus have a larger response at longer lead times. Finally, increased ocean resolution drives improvements to subseasonal predictability over Europe. This increase in skill seems to be a result of improvements to the Madden–Julian oscillation and its associated teleconnections rather than changes to air–sea interaction in the North Atlantic region.

The paper presents four ensembles of numerical experiments that compare the response to monopole and dipole heating perturbations resembling different phases of the Madden–Julian oscillation (MJO). The results quantify the Rossby and inertio-gravity (IG) wave response using the normal-mode function decomposition. The day 3 response is characterized by about 60% variance in the IG modes, with about 85% of it belonging to the Kelvin waves. On day 14, only 10% of the response variance is due to the Kelvin waves. Although the n = 1 Rossby mode is the main contributor to the Rossby variance at all time scales, the n > 1 Rossby modes contribute over 50% of the balanced response to the MJO heating. In the short range, dipole perturbations produce a response with the maximal variance in zonal wavenumbers k = 2–3 whereas in the medium range the response maximizes at k = 1 in all experiments. Furthermore, the medium-range response to the heating perturbation mimicking MJO phase 6 is found also over Europe.

Seasonal forecast skill of the basinwide and regional tropical cyclone (TC) activity in an experimental coupled prediction system based on the ECMWF System 4 is assessed. As part of a collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the ECMWF called Project Minerva, the system is integrated at the atmospheric horizontal spectral resolutions of T319, T639, and T1279. Seven-month hindcasts starting from 1 May for the years 1980–2011 are produced at all three resolutions with at least 15 ensemble members. The Minerva system demonstrates statistically significant skill for retrospective forecasts of TC frequency and accumulated cyclone energy (ACE) in the North Atlantic (NA), eastern North Pacific (EP), and western North Pacific. While the highest scores overall are achieved in the North Pacific, the skill in the NA appears to be limited by an overly strong influence of the tropical Pacific variability. Higher model resolution improves skill scores for the ACE and, to a lesser extent, the TC frequency, even though the influence of large-scale climate variations on these TC activity measures is largely independent of resolution changes. The biggest gain occurs in transition from T319 to T639. Significant skill in regional TC forecasts is achieved over broad areas of the Northern Hemisphere. The highest-resolution hindcasts exhibit additional locations with skill in the NA and EP, including land-adjacent areas. The feasibility of regional intensity forecasts is assessed. In the presence of the coupled model biases, the benefits of high resolution for seasonal TC forecasting may be underestimated.

This study examines El Niño–Southern Oscillation (ENSO) prediction in Project Minerva, a recent collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The focus is primarily on the impact of the atmospheric horizontal resolution on ENSO prediction, but the effect from different ensemble sizes is also discussed. Particularly, three sets of 7-month hindcasts performed with ECMWF prediction system are compared, starting from 1 May (1 November) during 1982–2011 (1982–2010): spectral T319 atmospheric resolution with 15 ensembles, spectral T639 with 15 ensembles, and spectral T319 with 51 ensembles. The analysis herein shows that simply increasing either ensemble size from 15 to 51 or atmospheric horizontal resolution from T319 to T639 does not necessarily lead to major improvement in the ENSO prediction skill with current climate models. For deterministic prediction skill metrics, the three sets of predictions do not produce a significant difference in either anomaly correlation or root-mean-square error (RMSE). For probabilistic metrics, the increased atmospheric horizontal resolution generates larger ensemble spread, and thus increases the ratio between the intraensemble spread and RMSE. However, there is little change in the categorical distributions of predicted SST anomalies, and consequently there is little difference among the three sets of hindcasts in terms of probabilistic metrics or prediction reliability.

The evolution of the Pacific subtropical cells (STC) is presented for the period 1948–2007. Using ocean models of different resolutions forced with interannually varying atmospheric forcing datasets, the mechanisms responsible for the observed STC weakening and late recovery during the period of study are analyzed. As a result of the STC weakening (strengthening), warming (cooling) trends are found in the equatorial Pacific sea surface temperatures (SSTs). Model results agree well with observed estimates of STC transport, STC convergence, and equatorial SST anomalies. It is shown that subtropical atmospheric variability is the primary driver of the STC and equatorial SST low-frequency evolution and is responsible for both the slowdown during the second half of the twentieth century and the rebound at the end of the century. Subtropically forced STC variability is identified as a major player in the generation of equatorial Pacific decadal SST anomalies, pacing tropical Pacific natural climate variability on interdecadal time scales, as observed in historical records. The natural mode of variability has implications for the evolution of equatorial SST in the coming decades under the concomitant effects of climate change.

processes that allows realistic and fast climate simula -tions that often involve large ensembles for the purpose of reducing uncertainty and estimation of the forced and internal variability of the system. The forced signal is typically estimated by an ensemble mean of many simulations, but ensembles of state-of-the-art models are often too small to reduce the remaining internal variability. The ensemble size needed to estimate the mean accurately depends on the signal-to-noise ratio for the variable and region under consideration. For example, the ensemble size to estimate midlatitude 500-hPa height accurately is about 20, which is larger than most ensembles used in seasonal hindcast data-sets or climate projections performed by individual centers. Intermediate complexity models can also be used efficiently to investigate the sensitivity of simu-lated climate to changes in parameters in the physical parameterizations. Another application is related to climate change. For example, Forest et al. (2002) and Sokolov at al. (2009) use the MIT Integrated Global System Model (MIT IGSM) to investigate topics such as climate sensitivity, aerosol forcing, ocean heat uptake rate, and probabilistic projections of climate change. There are many intermediate complexity system models of intermediate complexity (EMICs). A number of them are participating in the IPCC Fifth Assessment Report and can be found at http://climate .uvic.ca/EMICAR5 (one of which is based on a previous version of the model introduced here). This website also provides information about experiments that are performed with these models that range from en-sembles of 1,000-year-long historical simulations to the assessment of different CO

The Northern Hemisphere atmospheric circulation change from the 1960s to the 1990s shows a strong positive North Atlantic Oscillation (NAO) and a deepening of the Aleutian low. The issue regarding the contributions of external forcings and internal atmospheric variability to this circulation change has not been resolved satisfactorily. Previous studies have found the importance of tropical SST forcing. Here, this hypothesis is examined again using relatively large ensembles of atmospheric general circulation model simulations of the twentieth-century climate forced only by historically varying SST. The resulting ensemble-mean amplitude underestimates the observed change by at least 70%, although the spatial pattern is reproduced well qualitatively. Furthermore, AGCM experiments are performed to investigate other driving factors, such as the greenhouse gases, sea ice, the stratospheric ozone, as well as the contribution from atmospheric internal variability. The increase in ensemble-mean trend amplitude induced by these additional drivers was not enough to substantially improve the agreement with the observed trend. However, the full distribution of simulated trends reveals that the ensemble members at the upper tail are much closer to the observed amplitude. In the “best” ensemble, the 95th percentile of the simulated NAO trend amplitude remains at about 80% of the observed trend amplitude, with nearly equal contributions from external forcings and internal variability. The results also indicate that a complete set of driving factors and a correct simulation of stratospheric trends are important in bridging the gap between observed and modeled interdecadal variability in the North Atlantic winter circulation.

The 15-member ensembles of 46-day dynamical forecasts starting on each 15 May from 1991 to 2007 have been produced, using the ECMWF Variable Resolution Ensemble Prediction System monthly forecasting system (VarEPS-monthy). The dynamical model simulates a realistic interannual variability of Indian precipitation averaged over the month of June. It also displays some skill to predict Indian precipitation averaged over pentads up to a lead time of about 30 days. This skill exceeds the skill of the ECMWF seasonal forecasting System 3 starting on 1 June. Sensitivity experiments indicate that this is likely due to the higher horizontal resolution of VarEPS-monthly. Another series of sensitivity experiments suggests that the ocean–atmosphere coupling has an important impact on the skill of the monthly forecasting system to predict June rainfall over India.

The Indian monsoon–El Niño–Southern Oscillation (ENSO) relationship, according to which a drier than normal monsoon season precedes peak El Niño conditions, weakened significantly during the last two decades of the twentieth century. In this work an ensemble of integrations of an atmospheric general circulation model (AGCM) coupled to an ocean model in the Indian Basin and forced with observed sea surface temperatures (SSTs) elsewhere is used to investigate the causes of such a weakening. The observed interdecadal variability of the ENSO–monsoon relationship during the period 1950–99 is realistically simulated by the model and a dominant portion of the variability is associated with changes in the tropical Atlantic SSTs in boreal summer. In correspondence to ENSO, the tropical Atlantic SSTs display negative anomalies south of the equator in the last quarter of the twentieth century and weakly positive anomalies in the previous period. Those anomalies in turn produce heating anomalies, which excite a Rossby wave response in the Indian Ocean in both the model and the reanalysis data, impacting the time-mean monsoon circulation. The proposed mechanism of remote response of the Indian rainfall to tropical Atlantic sea surface temperatures is further tested forcing the AGCM coupled to the ocean model in the Indian Basin with climatological SSTs in the Atlantic Ocean and observed anomalies elsewhere. In this second ensemble the ENSO–monsoon relationship is characterized by a stable and strong anticorrelation through the whole second half of the twentieth century.

The circulation regimes in the Pacific–North American region are studied using the NCEP–NCAR reanalyses for the 18-winter period (1981/82–1998/99; NCEP18) and for the 54-winter period (1948/49–2001/02; NCEP54). The sampling properties of the regimes are estimated using very large ensembles (of size 55) of winter simulations made for the NCEP18 period with the atmospheric general circulation model of the Center for Ocean–Land–Atmosphere Studies, forced by observed SST and sea ice. The regimes are identified using a modified version of the k-means method. From the NCEP54 dataset a set of four clusters was found [i.e., the Alaskan ridge (AR), Arctic low (AL), Pacific trough (PT), and the Arctic high (AH)], which are significant (vis-à-vis a multinormal background), and more reproducible (within randomly chosen half-length samples) than would be expected from a multinormal process. The frequency of occurrence of the PT (AH) has increased (decreased) significantly during the past two decades. The PT cluster obtained from NCEP18 dataset more closely resembles the El Niño–forced seasonal mean pattern of recent decades than it does the traditional PNA. The GCM simulates the AR, AL, and PT clusters (but not the AH). The simulated AR and PT patterns have errors (cf. the NCEP18 results), which are outside the range of internal variability. The simulated frequency of occurrence agrees with the NCEP18 results within sampling variability. The differences in cluster properties of the PT and AR regimes between the NCEP18 and NCEP54 datasets are due to changes in SST forcing, not sampling error. Year-to-year changes in the frequency of occurrence of the PT, AL, and AR clusters in the simulations and the NCEP18 dataset are generally consistent with each other.

The atmospheric energy transport variability associated with decadal sea surface temperature variability in the tropical Pacific is studied using an atmospheric primitive equation model coupled to a slab mixed layer. The decadal variability is prescribed as an anomalous surface heat flux that represents the reduced ocean heat transport in the tropical Pacific when it is anomalously warm. The atmospheric energy transport increases and compensates for the reduced ocean heat transport. Increased transport by the mean meridional overturning (i.e., the strengthening of the Hadley cells) causes increased poleward energy transport. The subtropical jets increase in strength and shift equatorward, and in the midlatitudes the transients are affected. NCEP–NCAR reanalysis data show that the warming of the tropical Pacific in the 1980s compared to the early 1970s seems to have caused very similar changes in atmospheric energy transport indicating that these atmospheric transport variations were driven from the tropical Pacific. To study the implication of these changes for the coupled climate system an ocean model is driven with winds obtained from the atmosphere model. The poleward ocean heat transport increased when simulated wind anomalies associated with decadal tropical Pacific variability were used, showing a negative feedback between decadal variations in the mean meridional circulation in the atmosphere and in the Pacific Ocean. The Hadley cells and subtropical cells act to stabilize each other on the decadal time scale.

Using an atmosphere model of intermediate complexity and a hierarchy of ocean models, the dominant modes of interannual and decadal variability in the South Atlantic Ocean are studied. The atmosphere Simplified Parameterizations Primitive Equation Dynamics (SPEEDY) model has T30L7 resolution. The physical package consists of a set of simplified physical parameterization schemes, based on the same principles adopted in the schemes of state-of-the-art AGCMs. It is at least an order of magnitude faster, whereas the quality of the simulated climate compares well with those models. The hierarchy of ocean models consists of simple mixed layer models with an increasing number of physical processes involved such as Ekman transport, wind-induced mixing, and wind-driven barotropic transport. Finally, the atmosphere model is coupled to a regional version of the Miami Isopycnal Coordinate Ocean Model (MICOM) covering the South Atlantic with a horizontal resolution of 1° and 16 vertical layers. The coupled modes of mean sea level pressure and sea surface temperature simulated by SPEEDY–MICOM strongly resemble the modes as analyzed from the NCEP–NCAR reanalysis, indicating that this model configuration possesses the required physical mechanisms for generating these modes of variability. Using the ocean model hierarchy the authors were able to show that turbulent heat fluxes, Ekman transport, and wind-induced mixing contribute to the generation of the dominant modes of coupled SST variability. The different roles of these terms in generating these modes are analyzed. Variations in the wind-driven barotropic transport mainly seem to affect the SST variability in the Brazil–Malvinas confluence zone. The spectra of the mixed layer models appeared to be too red in comparison with the fully coupled SPEEDY–MICOM model due to the too strong coupling between SST and surface air temperatures (SATs), resulting from the inability to advect and subduct SST anomalies by the mixed layer models. In SPEEDY–MICOM anomalies in the southeastern corner of the South Atlantic are subducted and advected toward the north Brazilian coast on a time scale of about 6 yr.

The purpose of this paper is to study the influence of tropical sea surface temperature (SST) on the midlatitude circulation regime behavior in the Pacific–North American region. Toward this end, a cluster analysis has been applied to 55-member ensembles of winter seasonal simulations of the Center for Ocean–Land–Atmosphere Studies general circulation model for 18 winters. The ensemble members for each winter utilize the same prescribed, observed weekly varying SST for that winter. The cluster analysis includes all fluctuations with time scales longer than 10 days except for the ensemble mean seasonal cycle. Using a partitioning algorithm separately applied to each winter's ensemble, clusters are found in the 200-hPa height field that are signicant (vis-a-vis a suitable Gaussian background), reproducible (in half-length datasets), and consistent (with clusters obtained from the 200-hPa u wind) for all winters except the strong El Nino events of 1982/83, 1986/87, and 1997/98. One cluster found con...

The relationship between steady states of the large-scale flow regimes revealed by multimodality in phase space and quasi-resonant axes of a linearized atmospheric model (neutral vectors) is investigated by means of a hierarchy of three hemispheric quasigeostrophic(QG) models, in which the flow is relaxed toward a zonally symmetric equilibrium state and orography provides the only source of asymmetric forcing. Two of these models describe only the interaction between the mean zonal flow and planetary waves of zonal wavenumber 3, including one or two meridional wavenumbers. The third model also has a zonal wavenumber-3 symmetry, but includes waves up to total wavenumber 21, and therefore is able to properly represent the interactions between planetary waves and baroclinically unstable synoptic-scale waves. Three stationary solutions are found for the highly truncated models, two of which represent states with large wave amplitude but opposite phase. These two steady states produce two well-defined...

The role of high-frequency transients in the maintenance of planetary-scale flow regimes is investigated using a generalization of the neutral vector approach developed by Marshall and Molteni. Given a nonlinear dynamical model of the atmospheric motion, neutral vectors were defined as the axes with the smallest linear time derivative, computed by linearizing the equations of motion around the time-mean state of the system. If the nonlinear model possesses (at least) two steady states associated with nearly equally populated regimes, then the anomaly fields corresponding to the steady states strongly project onto the subspace spanned by the neutral vectors. The study of the simple nonlinear models with multiple steady solutions suggests that the nonlinear self-interactions of the high-frequency transients within each regime can shift the phase-space position of the regime mean state (or centroid) from the position of the corresponding steady state. If the feedback of high-frequency transients ont...

Linear instability analysis is applied to study the role of barotropic dynamics in the evolution of blocking events during winter 1990/91. Finite-time interval instabilities (i.e., nonnormal-mode structures defined as the singular vectors of the tangent propagator) growing over periods of 4 days have been computed using adjoint methods. Correlation between large values of the singular vector amplification rate and the occurrence of blocking onset in the real atmosphere is studied. A correspondence is found between periods with the largest singular vector amplification rates and periods either leading to blocking formation or covering the mature phase of blocks. It is shown that at final time the singular vectors tend to have largest amplitude in the same regions of planetary wave ridging where blocks develop. On average, singular vectors developing on the Pacific have larger growth rates than those in the Euro–Atlantic region. The analysis of some case studies indicates a qualitative similarity b...

Properties of the general circulation simulated by the ECMWF model are discussed using a set of seasonal integrations at T63 resolution. For each season, over the period of 5 years, 1986–1990, three integrations initiated on consecutive days were run with prescribed observed sea surface temperature (SST). This paper presents a series of diagnostics of extratropical variability in the model, with particular emphasis on the northern winter. Time-filtered maps of variability indicate that in this season there is insufficient storm track activity penetrating into the Eurasian continent. Related to this the maximum of lower-frequency variance in the Euro-Atlantic region is erroneously shifted eastward in the model. By contrast the simulated fields of both high- and low-frequency variability for northern spring are more realistic. Blocking is defined objectively in terms of the geostrophic wind at 500 mb. Consistent with the low-frequency transience, in the Euro-Atlantic sector the position of maximum ...

A strategy for diagnosing and interpreting flow regimes that is firmly rooted in dynamical theory is presented and applied to the study of observed and modeled planetary-scale regimes of the wintertime circulation in the Northern Hemisphere. The method assumes a nonlinear dynamical model of the atmospheric motion, and determines a subspace of the phase space of the model in which multiple quasi-stationary solutions of the equations of motion are likely to be located. The axes that generate this subspace are the vectors that possess the smallest amplitude of the time derivative computed from a linearized version of the model, using the time-mean state of the system as a basic state. These vectors are called here “neutral vectors,” and are shown to be eigenvectors of a self-adjoint operator derived from the linearized model. As a prototype of a dynamical system with quadratic nonlinearity relevant to atmospheric dynamics, the three-variable convection model that generates the well-known Lorenz attr...

During the winter of 1988/89, a real-time experimental scheme to predict skill of the ECMWF operational forecast was devised. The scheme was based on statistical relations between skill scores (the predictands) and a number of predictors including consistency between consecutive forecasts, amplitude of very short-range forecast errors, and indices of large-scale regime transitions. The results of the experiment are assessed with particular attention to a period with large variations in the skill of the operational forecast. -Authors

Principal component analysis is used to study the rainfall distribution over northern Italy in the cold season (October-April). A spatial analysis is applied to the squares roots of daily data, recorded in 14 months, and of their 3- and 5-day means, working on cross-product matrices obtained from both standardized and nonstandardized values. Four principal components (PCs) can be selected: the first is an index of the mean rainfall; the second represents the longitudinal differences; the third and fourth are representative of orographic anomalies. For daily data, these 4 PCs account for more than 80% of the total variance (since cross-product matrices are used in the analysis the term variance must be interpreted as mean square value); this percentage is slightly higher working on nonstandardized values, but with standardized values the explained variance is distributed more uniformly among the 35 rainfall stations. Passing to 3- and 5-day means, the cumulative variance of the first 4 PCs increas...