Search for: All records

Abstract 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. 

Abstract Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_LO, and SPEAR_MED dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen and Bellingshausen, Indian, and West Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently-developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal timescales. 

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.

 

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.