European and eastern United States wintertime weather is strongly influenced by large‐scale modes of variability in the Northern Hemisphere such as the Arctic Oscillation (AO) and North Atlantic ...Oscillation (NAO). The negative phase of the NAO has been linked to both the Madden‐Julian Oscillation (MJO) phase with convection in the West Pacific (phases 6 and 7) and to stratospheric sudden warmings (SSW), but the relative role of each phenomenon is not clear, and the two phenomena are themselves linked, as more than half of SSW events were preceded by phases 6 and 7 of the MJO. Here we disentangle the relative roles of MJO phase 6/7 and stratospheric variability for Northern Hemisphere surface weather during boreal winter. We show that stratospheric variability leads to significantly different North Atlantic anomalies if it is preceded by MJO phase 6/7. Furthermore, MJO phase 6/7 leads to a long‐lived negative AO pattern only if it modulates the stratosphere first. Hence, proper attribution of their respective influence on surface weather needs to take into consideration the linkages between these two phenomena. Finally, MJO phase 6/7 events that lead to SSW can be differentiated from those which do not by their characteristics within the tropics: only MJO phase 6/7 events in which enhanced convection propagates into the South China Sea, which rarely occurs in winter, lead to SSWs.
Key Points
More than half of SSWs were preceded by MJO phase 6/7, and hence the relative role of each phenomenon for NH climate needs clarification
MJO phase 6/7 leads to a strong and long‐lived negative AO only if it modulates the stratosphere first
Some of the surface impacts of the SSW are likely due to the lingering aftereffects of MJO phase 6/7 that helped force the SSW
A minor sudden stratospheric warming (SSW) happened in September 2019 in the Southern Hemisphere (SH) with winds at 10 hPa, 60°S reaching their minimum value on 18 September. Using multiple data sets ...and real‐time predictions from 11 subseasonal to seasonal (S2S) models, the evolution, favorable conditions, and predictability for this SSW event are explored. The September 2019 SSW happened during several favorable conditions, including easterly equatorial quasi‐biennial oscillation (QBO) winds at 10 hPa, solar minimum, positive Indian Ocean Dipole (IOD) sea surface temperatures (SST), warm SST anomalies in the central Pacific, and a blocking high near the Antarctic Peninsula. With these favorable initial and boundary conditions, the predictive limit to this SSW is around 18 days in some S2S models, and more than 50% of the ensemble members forecast the zonal wind deceleration in reforecasts initialized around 29 August. A vortex slowdown is evident in some initializations from around 22 August, but with a forecast‐reanalysis pattern correlation %3C0.5, while initializations later than 29 August capture the wavelike pattern in the troposphere and the subsequent stratospheric evolution. The ensemble spread in the magnitude of the vortex deceleration during the SSW is mainly explained by the ensemble spread in the magnitude of upward propagation of waves in the troposphere and in the stratosphere, with an underestimated tropospheric wave amplitude leading to a too‐small deceleration of the vortex. The September 2019 SH SSW did not show a near‐instantaneous downward impact on the tropospheric southern annular mode (SAM) in late September and early October 2019. The Australian drought and hot weather in September possibly associated with the positive IOD might have been exacerbated by the negative SAM in October and later months due to the weak stratospheric polar vortex. However, models tend to forecast a near‐instantaneous tropospheric response to the SSW.
Key Points
An SH SSW happened in September 2019, with westerly winds at 10 hPa, 50°S reversed on 16 September
This SH SSW appeared during several favorable conditions, including easterly QBO winds, solar minimum, positive IOD, and warm SST anomalies in the central Pacific
The predictive limit to this SSW is ~18 days in some S2S models, but models forecast a faster tropospheric response to the SSW than observations
The response of the early winter Northern Hemisphere stratospheric polar vortex and tropospheric Arctic Oscillation to anomalous autumn snow cover in Eurasia is evaluated in four operational ...subseasonal forecasting models. Of these four models, the two with finer stratospheric resolution simulate a weakened vortex for hindcasts initialized with more extensive snow as compared to those with less extensive snow, consistent with the observed effect, though the modeled effect is significantly weaker than that observed. The other two models fail to capture the local Western Eurasian ridge in response to enhanced snow, and hence their failure to simulate a stratospheric response may be due to biases in representing surface–atmosphere coupling rather than their coarser stratospheric resolution per se. There is no evidence of a tropospheric Arctic Oscillation response in early winter in any of these models, which may be related to the weakness of the stratospheric response or (in one model) to too-weak coupling from the stratosphere down to the surface. Overall, the possible contribution of autumn snowcover over Eurasia to improved predictability of the winter Arctic Oscillation in subseasonal forecast models has not yet been realized even in a probabilistic sense.
The stratosphere can have a significant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to ...capture two important links between the stratosphere and troposphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Probabilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Pacific and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Niño–Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the United States, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions.
Key Points
Tropospheric precursors of SSW events are better represented for the North Pacific than for Eurasia
Teleconnections from the tropics add probabilistic skill but are only represented by a few models
Weak and strong vortex events in the NH stratosphere can contribute to surface skill 3–4 weeks later
The representation of upward and downward stratosphere‐troposphere coupling and its influence on the teleconnections of the Madden‐Julian oscillation (MJO) to the European sector is examined in five ...subseasonal‐to‐seasonal models. We show that while the models simulate a realistic stratospheric response to transient anomalies in troposphere, they overestimate the downward coupling. The models with a better stratospheric resolution capture a more realistic stratospheric response to the MJO, particularly after the first week of the integration. However, in all models examined here the connection between the MJO and vortex variability is weaker than that observed. Finally, we focus on the MJO‐SSW (sudden stratospheric warming) teleconnection and specifically initializations during the MJO phase with enhanced convection in the west/central pacific (i.e., 6 and 7) that preceded observed SSW. The integrations that simulated a SSW (as observed) can be distinguished from those that failed to simulate a SSW by the realism of the Pacific response to MJO 6/7, with only the simulations that successfully simulate a SSW capturing the North Pacific low. Furthermore, only the simulations that capture the SSW subsequently simulate a realistic surface response over the North Atlantic and Europe.
Key Points
The S2S models are able to capture the stratosphere‐troposphere upward coupling. However, the downward coupling is overestimated
The models with a better stratospheric resolution capture the stratospheric response to the MJO, although it is weaker than the observed
Integrations that simulated the observed SSW associated with MJO 6/7, also simulated a realistic North Pacific response to the MJO
The stratosphere has been identified as an important source of predictability for a range of processes on subseasonal to seasonal (S2S) time scales. Knowledge about S2S predictability within the ...stratosphere is however still limited. This study evaluates to what extent predictability in the extratropical stratosphere exists in hindcasts of operational prediction systems in the S2S database. The stratosphere is found to exhibit extended predictability as compared to the troposphere. Prediction systems with higher stratospheric skill tend to also exhibit higher skill in the troposphere. The analysis also includes an assessment of the predictability for stratospheric events, including early and midwinter sudden stratospheric warming events, strong vortex events, and extreme heat flux events for the Northern Hemisphere and final warming events for both hemispheres. Strong vortex events and final warming events exhibit higher levels of predictability as compared to sudden stratospheric warming events. In general, skill is limited to the deterministic range of 1 to 2 weeks. High‐top prediction systems overall exhibit higher stratospheric prediction skill as compared to their low‐top counterparts, pointing to the important role of stratospheric representation in S2S prediction models.
Key Points
High‐top models have more skill in the stratosphere and the troposphere compared to low‐top models
Extreme stratospheric events are predictable at 1‐ to 2‐week lead times in S2S models
SSW events tend to be less predictable than strong vortex events or final warming events
The effect of the Quasi‐Biennial Oscillation (QBO) on the Northern Hemisphere wintertime stratospheric polar vortex is evaluated in five operational subseasonal forecasting models. Of these five ...models, the three with the best stratospheric resolution all indicate a weakened vortex during the easterly phase of the QBO relative to its westerly phase, consistent with the Holton‐Tan effect. The magnitude of this effect is well captured for initializations in late October and November in the model with the largest ensemble size. While the QBO appears to modulate the extratropical tropospheric circulation in some of the models as well, the importance of a polar stratospheric pathway, through the Holton‐Tan effect, for the tropospheric anomalies is unclear. Overall, knowledge of the QBO can contribute to enhanced predictability, at least in a probabilistic sense, of the Northern Hemisphere winter climate on subseasonal timescales.
Plain Language Summary
The Quasi‐Biennial Oscillation (QBO) is perhaps the most regular atmospheric phenomena that is not directly controlled by solar radiation and can be predicted more than a year in advance. It is characterized by alternating westerly and easterly winds in the tropical stratosphere. Here we show that the QBO can be used to improve month‐ahead prediction of the Northern Hemisphere wintertime stratospheric polar vortex, and perhaps even the extratropical tropospheric circulation.
Key Points
QBO can contribute to enhanced predictability, in a probabilistic sense, of the Northern Hemisphere climate on subseasonal timescales
Operational subseasonal forecasting models with reasonable stratospheric resolution capture the Holton‐Tan effect
Anomalies may propagate down to surface, though some ambiguities exist
Abstract
Teleconnection patterns associated with the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO) impact weather and climate phenomena in the Pacific–North American region ...and beyond, and therefore accurately simulating these teleconnections is of importance for seasonal and subseasonal forecasts. Systematic biases in boreal midwinter ENSO and MJO teleconnections are found in eight subseasonal to seasonal (S2S) forecast models over the Pacific–North America region. All models simulate an anomalous 500-hPa geopotential height response that is too weak. This overly weak response is associated with overly weak subtropical upper-level convergence and a too-weak Rossby wave source in most models, and in several models there is also a biased subtropical Pacific jet, which affects the propagation of Rossby waves. In addition to this overly weak response, all models also simulate ENSO teleconnections that reach too far poleward toward Alaska and northeastern Russia. The net effect is that these models likely underestimate the impacts associated with the MJO and ENSO over western North America, and suffer from a reduction in skill from what could be achieved.
Abstract
A yet unexplained feature of the tropical wavenumber-frequency spectrum is its parity distributions, i.e., the distribution of power between the meridionally symmetric and anti-symmetric ...components of the spectrum. Due to the linearity of the decomposition to symmetric and anti-symmetric components and the Fourier analysis, the total spectral power equals the sum of the power contained in each of these two components. However, the spectral power need not be evenly distributed between the two components. Satellite observations and reanalysis data provide ample evidence that the parity distribution of the tropical wavenumber-frequency spectrum is biased towards its symmetric component. Using an intermediate-complexity model of an idealized moist atmosphere, we find that the parity distribution of the tropical spectrum is nearly insensitive to large-scale forcing, including topography, ocean heat fluxes, and land-sea contrast. On the other hand, we find that a small-scale (stochastic) forcing has the capacity to affect the parity distribution at large spatial scales via an upscale (inverse) turbulent energy cascade. These results are qualitatively explained by considering the effects of triad interactions on the parity distribution. According to the proposed mechanism, any bias in the small-scale forcing, symmetric or anti-symmetric, leads to symmetric bias in the large-scale spectrum regardless of the source of variability responsible for the onset of the asymmetry. As this process is also associated with the generation of large-scale features in the Tropics by small-scale convection, the present study demonstrates that the physical process associated with deep-convection leads to a symmetric bias in the tropical spectrum.
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