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In this study, we examine the wintertime environmental precursors of summer anticyclonic wave breaking (AWB) over the North Atlantic region and assess the applicability of these precursors in predicting AWB impacts on seasonal tropical cyclone (TC) activity. We show that predictors representing the environmental impacts of subtropical AWB on seasonal TC activity improve the skill of extended-range seasonal forecasts of TC activity. There is a significant correlation between boreal winter and boreal summer AWB activity via AWB-forced phases of the quasi-stationary North Atlantic Oscillation (NAO). Years with above-normal boreal summer AWB activity over the North Atlantic region also show above-normal AWB activity in the preceding boreal winter that tends to force a positive phase of the NAO that persists through the spring. These conditions are sustained by continued AWB throughout the year, particularly when El Niño–Southern Oscillation plays less of a role at forcing the large-scale circulation. While individual AWB events are synoptic and nonlinear with little predictability beyond 8–10 days, the strong dynamical connection between winter and summer wave breaking lends enough persistence to AWB activity to enable predictability of its potential impacts on TC activity. We find that the winter–summer relationship improves the skill of extended-range seasonal forecasts from as early as an April lead time, particularly for years when wave breaking has played a crucial role in suppressing TC development.

The excitation of the Pacific–North American (PNA) teleconnection pattern by the Madden–Julian oscillation (MJO) has been considered one of the most important predictability sources on subseasonal time scales over the extratropical Pacific and North America. However, until recently, the interactions between tropical heating and other extratropical modes and their relationships to subseasonal prediction have received comparatively little attention. In this study, a linear inverse model (LIM) is applied to examine the tropical–extratropical interactions. The LIM provides a means of calculating the response of a dynamical system to a small forcing by constructing a linear operator from the observed covariability statistics of the system. Given the linear assumptions, it is shown that the PNA is one of a few leading modes over the extratropical Pacific that can be strongly driven by tropical convection while other extratropical modes present at most a weak interaction with tropical convection. In the second part of this study, a two-step linear regression is introduced that leverages a LIM and large-scale climate variability to the prediction of hydrological extremes (e.g., atmospheric rivers) on subseasonal time scales. Consistent with the findings of the first part, most of the predictable signals on subseasonal time scales are determined by the dynamics of the MJO–PNA teleconnection while other extratropical modes are important only at the shortest forecast leads.

The Madden–Julian oscillation (MJO) excites strong variations in extratropical geopotential heights that modulate extratropical weather, making the MJO an important predictability source on subseasonal to seasonal time scales (S2S). Previous research demonstrates a strong similarity of teleconnection patterns across MJO events for certain MJO phases (i.e., pattern consistency) and increased model ensemble agreement during these phases that is beneficial for extended numerical weather forecasts. However, the MJO’s ability to modulate extratropical weather varies greatly on interannual time scales, which brings extra uncertainty in leveraging the MJO for S2S prediction. Few studies have investigated the mechanisms responsible for variations in the consistency of MJO tropical–extratropical teleconnections on interannual time scales. This study uses reanalysis data, ensemble simulations of a linear baroclinic model, and a Rossby wave ray tracing algorithm to demonstrate that two mechanisms largely determine the interannual variability of MJO teleconnection consistency. First, the meridional shift of stationary Rossby wave ray paths indicates increases (decreases) in the MJO’s extratropical modulation during La Niña (El Niño) years. Second, a previous study proposed that the constructive interference of Rossby wave signals caused by a dipole Rossby wave source pattern across the subtropical jet during certain MJO phases produces a consistent MJO teleconnection. However, this dipole feature is less clear in both El Niño and La Niña years due to the extension and contraction of MJO convection, respectively, which would decrease the MJO’s influence in the extratropics. Hence, considering the joint influence of the basic state and MJO forcing, this study suggests a diminished potential to leverage the MJO for S2S prediction in El Niño years.

The Madden–Julian oscillation (MJO) is one of the most important sources of predictability on subseasonal to seasonal (S2S) time scales. Many previous studies have explored the impact of the present state of the MJO on the future evolution and predictability of extratropical weather patterns. What is still unclear, however, is the importance of the accumulated influence of past MJO activity on these results. In this study, the importance of past MJO activity in determining the future state of extratropical circulations is examined by using a linear baroclinic model (LBM) and one of the simplest machine learning algorithms: logistic regression. By increasing the complexity of the logistic regression model with additional information about the past activity of the MJO, it is demonstrated that the past 15 days play a dominant role in determining the state of MJO teleconnections more than 15 days into the future. This conclusion is supported by numerical LBM simulations. It is further shown that the past 15 days of additional information are only important for some MJO phases/lead times and not others, and the physical basis for this result is explored.

Arctic–midlatitude teleconnections are complex and multifaceted. By design, targeted modeling studies typically focus only on one direction of influence—usually, the midlatitude atmospheric response to a changing Arctic. The two-way, coupled feedbacks between the Arctic and the midlatitude circulation on submonthly time scales are explored using a regularized regression model formulated around Granger causality. The regularized regression model indicates that there are regions in which Arctic temperature drives a midlatitude circulation response, and regions in which the midlatitude circulation drives a response in the Arctic; however, these regions rarely overlap. In many regions, on submonthly time scales, the midlatitude circulation drives Arctic temperature variability, highlighting the important role the midlatitude circulation can play in impacting the Arctic. In particular, the regularized regression model results support recent work that indicates that the observed high pressure anomalies over Eurasia drive a significant response in the Arctic on submonthly time scales, rather than being driven by the Arctic.

Previous studies have suggested that, in the zonal mean, the climatological Northern Hemisphere wintertime eddy-driven jet streams will weaken and shift equatorward in response to Arctic amplification and sea ice loss. However, multiple studies have also pointed out that this response has strong regional differences across the two ocean basins, with the North Atlantic jet stream generally weakening across models and the North Pacific jet stream showing signs of strengthening. Based on the zonal wind response with a fully coupled model, this work sets up two case studies using a barotropic model to test a dynamical mechanism that can explain the differences in zonal wind response in the North Pacific versus the North Atlantic. Results indicate that the differences between the two basins are due, at least in part, to differences in the proximity of the jet streams to the sea ice loss, and that in both cases the eddies act to increase the jet speed via changes in wave breaking location and frequency. Thus, while baroclinic arguments may account for an initial reduction in the midlatitude winds through thermal wind balance, eddy–mean flow feedbacks are likely instrumental in determining the final total response and actually act to strengthen the eddy-driven jet stream.

The Madden–Julian oscillation (MJO) excites strong variations in extratropical atmospheric circulations that have important implications for subseasonal-to-seasonal (S2S) prediction. A previous study showed that particular MJO phases are characterized by a consistent modulation of geopotential heights in the North Pacific and adjacent regions across different MJO events, and demonstrated that this consistency is beneficial for extended numerical weather forecasts (i.e., lead times of two weeks to one month). In this study, we examine the physical mechanisms that lead some MJO phases to have more consistent teleconnections than others using a linear baroclinic model. The results show that MJO phases 2, 3, 6, and 7 consistently generate Pacific–North American (PNA)-like patterns on S2S time scales while other phases do not. A Rossby wave source analysis is applied and shows that a dipole-like pattern of Rossby wave source on each side of the subtropical jet can increase the pattern consistency of teleconnections due to the constructive interference of similar teleconnection signals. On the other hand, symmetric patterns of Rossby wave source can dramatically reduce the pattern consistency due to destructive interference. A dipole-like Rossby wave source pattern is present most frequently when tropical heating is found in the Indian Ocean or the Pacific warm pool, and a symmetric Rossby wave source is present most frequently when tropical heating is located over the Maritime Continent. Thus, the MJO phase-dependent pattern consistency of teleconnections is a special case of this mechanism.

Multidecadal variability in the North Atlantic jet stream in general circulation models (GCMs) is compared with that in reanalysis products of the twentieth century. It is found that almost all models exhibit multidecadal jet stream variability that is entirely consistent with the sampling of white noise year-to-year atmospheric fluctuations. In the observed record, the variability displays a pronounced seasonality within the winter months, with greatly enhanced variability toward the late winter. This late winter variability exceeds that found in any GCM and greatly exceeds expectations from the sampling of atmospheric noise, motivating the need for an underlying explanation. The potential roles of both external forcings and internal coupled ocean–atmosphere processes are considered. While the late winter variability is not found to be closely connected with external forcing, it is found to be strongly related to the internally generated component of Atlantic multidecadal variability (AMV) in sea surface temperatures (SSTs). In fact, consideration of the seasonality of the jet stream variability within the winter months reveals that the AMV is far more strongly connected to jet stream variability during March than the early winter months or the winter season as a whole. Reasoning is put forward for why this connection likely represents a driving of the jet stream variability by the SSTs, although the dynamics involved remain to be understood. This analysis reveals a fundamental mismatch between late winter jet stream variability in observations and GCMs and a potential source of long-term predictability of the late winter Atlantic atmospheric circulation.

Previous studies have found that the most consistent response of the eddy-driven jet to sea ice loss and Arctic amplification in fully coupled general circulation models (GCMs) is a broad region of anomalous easterlies on the poleward flank. In this study, a similar response is noted in a dry dynamical core GCM with imposed surface heating at the pole, and it is shown that in both a fully coupled GCM’s North Atlantic basin and the dry dynamical core, the anomalous easterlies cause an asymmetrical narrowing of the jet on the poleward flank of the climatological jet. A suite of barotropic model simulations run with polar forcing shows decreased jet positional variability consistent with a narrowing of the jet profile, and it is proposed that this narrowing decreases the distance Rossby waves can propagate away from the jet core, which drives changes in jet variability. Since Rossby wave propagation and dissipation is intrinsic to the development and maintenance of the eddy-driven jet, and is tightly coupled to a jet’s variability, this acts as a meridional constraint on waves’ ability to propagate outside of the jet core, leading to the decreased variability in zonal-mean jet position. The results from all three models demonstrates that this relationship is present across a model hierarchy.

In climate variability studies, lagged linear regression is frequently used to infer causality. While lagged linear regression analysis can often provide valuable information about causal relationships, lagged regression is also susceptible to overreporting significant relationships when one or more of the variables has substantial memory (autocorrelation). Granger causality analysis takes into account the memory of the data and is therefore not susceptible to this issue. A simple Monte Carlo example highlights the advantages of Granger causality, compared to traditional lagged linear regression analysis in situations with one or more highly autocorrelated variables. Differences between the two approaches are further explored in two illustrative examples applicable to large-scale climate variability studies. Given that Granger causality is straightforward to calculate, Granger causality analysis may be preferable to traditional lagged regression analysis when one or more datasets has large memory.

Near-surface Arctic warming has been shown to impact the midlatitude jet streams through the use of carefully designed model simulations with and without Arctic sea ice loss. In this work, a Granger causality regression approach is taken to quantify the response of the zonal wind to variability of near-surface Arctic temperatures on subseasonal time scales across the CMIP5 models. Using this technique, a robust influence of regional Arctic warming on the North Atlantic and North Pacific jet stream positions, speeds, and zonal winds is demonstrated. However, Arctic temperatures only explain an additional 3%–5% of the variance of the winds after accounting for the variance associated with the persistence of the wind anomalies from previous weeks. In terms of the jet stream response, the North Pacific and North Atlantic jet streams consistently shift equatorward in response to Arctic warming but also strengthen, rather than weaken, during most months of the year. Furthermore, the sensitivity of the jet stream position and strength to Arctic warming is shown to be a strong function of season. Specifically, in both ocean basins, the jets shift farthest equatorward in the summer months. It is argued that this seasonal sensitivity is due to the Arctic-warming-induced wind anomalies remaining relatively fixed in latitude, while the climatological jet migrates in and out of the anomalies throughout the annual cycle. Based on these results, model differences in the climatological jet stream position are shown to lead to differences in the jet stream position’s sensitivity to Arctic warming.

A dry dynamical core is used to investigate the seasonal sensitivity of the circulation to two idealized thermal forcings: a tropical upper-tropospheric heating and a polar lower-tropospheric heating. The thermal forcings are held constant, and the response of the circulation in each month of the year is explored. First, the circulation responses to tropical warming and polar warming are studied separately, and then the response to the simultaneously applied forcings is analyzed. Finally, the seasonality of the internal variability of the circulation is explored as a possible mechanism to explain the seasonality of the responses. The primary results of these experiments are as follows: 1) There is a seasonal sensitivity in the circulation response to both the tropical and polar forcings. 2) The jet position response to each forcing is greatest in the transition seasons, and the jet speed response exhibits a seasonal sensitivity to both forcings, although the seasonal sensitivities are not the same. 3) The circulation response is nonlinear in the transition seasons, but approximately linear in the winter months. 4) The internal variability of the unforced circulation exhibits a seasonal sensitivity that may partly explain the seasonal sensitivity of the forced response. The seasonality of the internal variability of daily MERRA reanalysis data is compared to that of the model, demonstrating that the broad conclusions drawn from this idealized modeling study may be useful for understanding the jet response to anthropogenic forcing.

Recent work on atmospheric rivers (ARs) has led to a characterization of these impactful features as primarily cold-season phenomena. Here, an all-season analysis of AR incidence in the North Pacific basin is performed for the period spanning 1979–2014 using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis dataset. An occurrence-based detection algorithm is developed and employed to identify and characterize ARs in instantaneous fields of anomalous vertically integrated water vapor transport. The all-season climatology and variability of AR frequencies due to the seasonal cycle, the El Niño–Southern Oscillation (ENSO), the Madden–Julian oscillation (MJO), and their interactions are presented based on composites of the detected features. The results highlight that ARs exist throughout the year over the North Pacific, although their preferred locations shift substantially throughout the year. This seasonal cycle manifests itself as northward and westward displacement of ARs during the Northern Hemisphere warm seasons, rather than an absolute change in the number of ARs within the domain. It is also shown that changes to the North Pacific mean-state due to ENSO and the MJO may enhance or completely offset the seasonal cycle of AR activity, but that such influences on AR frequencies vary greatly based on location.

The volcanic eruption of Mount Pinatubo in June 1991 is the largest terrestrial eruption since the beginning of the satellite era. Here, the monthly evolution of atmospheric temperature, zonal winds, and precipitation following the eruption in 14 CMIP5 models is analyzed and strong and robust stratospheric and tropospheric circulation responses are demonstrated in both hemispheres, with tropospheric anomalies maximizing in November 1991. The simulated Southern Hemisphere circulation response projects strongly onto the positive phase of the southern annular mode (SAM), while the Northern Hemisphere exhibits robust North Atlantic and North Pacific responses that differ significantly from that of the typical northern annular mode (NAM) pattern. In contrast, observations show a negative SAM following the eruption, and internal variability must be considered along with forced responses. Indeed, evidence is presented that the observed El Niño climate state during and after this eruption may oppose the eruption-forced positive SAM response, based on the El Niño–Southern Oscillation (ENSO) state and SAM response across the models. The results demonstrate that Pinatubo-like eruptions should be expected to force circulation anomalies across the globe and highlight that great care must be taken in diagnosing the forced response as it may not fall into typical seasonal averages or be guaranteed to project onto typical climate modes.

The persistent and quasi-stationary nature of atmospheric blocking is associated with long-lasting extreme weather conditions that influence much of the Northern Hemisphere during boreal winter. The Madden–Julian oscillation (MJO) has been previously shown to influence important factors for blocking, including Rossby wave breaking and the North Atlantic Oscillation (NAO). However, the extent to which the MJO influences blocking across the Northern Hemisphere is not yet fully understood. Utilizing a two-dimensional blocking index, composites of North Pacific, North Atlantic, and European blocking are generated relative to MJO phase. In the west and central Pacific, all MJO phases demonstrate significant changes in blocking, particularly at high latitudes. A significant decrease in east Pacific and Atlantic blocking occurs following phase 3 of the MJO, characterized by enhanced convection over the tropical East Indian Ocean and suppressed convection in the west Pacific. The opposite-signed MJO heating during phase 7 is followed by a significant increase in east Pacific and Atlantic blocking. A significant decrease in European blocking follows MJO phase 4, with an increase after phase 6. The phase 6 European blocking is hypothesized to result from two preexisting conditions: 1) an anomalous anticyclone over the Atlantic and 2) a preceding negative Pacific–North American (PNA) pattern initialized and influenced by MJO heating.

Two common approaches for estimating a linear trend are 1) simple linear regression and 2) the epoch difference with possibly unequal epoch lengths. The epoch difference estimator for epochs of length M is defined as the difference between the average value over the last M time steps and the average value over the first M time steps divided by N − M, where N is the length of the time series. Both simple linear regression and the epoch difference are unbiased estimators for the trend; however, it is demonstrated that the variance of the linear regression estimator is always smaller than the variance of the epoch difference estimator for first-order autoregressive [AR(1)] time series with lag-1 autocorrelations less than about 0.85. It is further shown that under most circumstances if the epoch difference estimator is applied, the optimal epoch lengths are equal and approximately one-third the length of the time series. Additional results are given for the optimal epoch length at one end when the epoch length at the other end is constrained.

Internal variability in the climate system gives rise to large uncertainty in projections of future climate. The uncertainty in future climate due to internal climate variability can be estimated from large ensembles of climate change simulations in which the experiment setup is the same from one ensemble member to the next but for small perturbations in the initial atmospheric state. However, large ensembles are invariably computationally expensive and susceptible to model bias. Here the authors outline an alternative approach for assessing the role of internal variability in future climate based on a simple analytic model and the statistics of the unforced climate variability. The analytic model is derived from the standard error of the regression and assumes that the statistics of the internal variability are roughly Gaussian and stationary in time. When applied to the statistics of an unforced control simulation, the analytic model provides a remarkably robust estimate of the uncertainty in future climate indicated by a large ensemble of climate change simulations. To the extent that observations can be used to estimate the amplitude of internal climate variability, it is argued that the uncertainty in future climate trends due to internal variability can be robustly estimated from the statistics of the observed climate.

Recent studies have hypothesized that Arctic amplification, the enhanced warming of the Arctic region compared to the rest of the globe, will cause changes in midlatitude weather over the twenty-first century. This study exploits the recently completed phase 5 of the Coupled Model Intercomparison Project (CMIP5) and examines 27 state-of-the-art climate models to determine if their projected changes in the midlatitude circulation are consistent with the hypothesized impact of Arctic amplification over North America and the North Atlantic. Under the largest future greenhouse forcing (RCP8.5), it is found that every model, in every season, exhibits Arctic amplification by 2100. At the same time, the projected circulation responses are either opposite in sign to those hypothesized or too widely spread among the models to discern any robust change. However, in a few seasons and for some of the circulation metrics examined, correlations are found between the model spread in Arctic amplification and the model spread in the projected circulation changes. Therefore, while the CMIP5 models offer some evidence that future Arctic warming may be able to modulate some aspects of the midlatitude circulation response in some seasons, the analysis herein leads to the conclusion that the net circulation response in the future is unlikely to be determined solely—or even primarily—by Arctic warming according to the sequence of events recently hypothesized.

The correlation lengths of vorticity anomalies from temporal averages are examined in the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis dataset. It is shown that, in the annual mean, eddies in the Southern Hemisphere are significantly larger than those in the Northern Hemisphere. The eddy vorticity lengths exhibit a strong seasonal cycle, with the largest scales occurring in the winter season. The maximum zonal eddy lengths closely follow the contours of the strong upper-level winds, while the maximum meridional lengths are found in jet exit regions and in the stratosphere.