2019
DOI: 10.1175/jas-d-18-0179.1
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The Impact of the QBO on MJO Convection in Cloud-Resolving Simulations

Abstract: This study examines the relationship between the Madden–Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO) in a limited-area cloud-resolving model with parameterized large-scale dynamics. The model is used to simulate two consecutive MJO events that occurred during the late fall and early winter of 2011. To test the influence of the QBO on the simulated MJO events, various QBO states are imposed via the addition of characteristic wind and temperature anomalies. In experiments with … Show more

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Cited by 49 publications
(58 citation statements)
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References 77 publications
(112 reference statements)
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“…While small compared to observations and control runs, the results are significant for 2–3 weeks, beginning around 15 days after initialization (e.g., Figures ), and further are significant if the MJO amplitude is averaged over Days 0–30 (Figure ). The MJO amplitude change in the imposed‐QBO experiments is stronger when the 100‐hPa tropically averaged temperature difference is larger (i.e., is colder in imposed‐QBOE compared to imposed‐QBOW; Figure ). This suggests, though does not conclusively show, that 100‐hPa QBO‐related temperature anomalies may drive the strengthening of the MJO, as has been proposed and supported by other studies (Hendon & Abhik, ; Martin et al, ; Son et al, ). In imposed‐QBO experiments where the MJO is strong and initialized in Phase 4, there is still a weak but significant MJO response despite the smaller sample size, especially when the MJO is in Phases 6–8 (Figures and ). Differences in other subsets of experiments, such as strong, Phase 2 MJO events, show no significant response (Figure ).…”
Section: Discussionmentioning
confidence: 60%
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“…While small compared to observations and control runs, the results are significant for 2–3 weeks, beginning around 15 days after initialization (e.g., Figures ), and further are significant if the MJO amplitude is averaged over Days 0–30 (Figure ). The MJO amplitude change in the imposed‐QBO experiments is stronger when the 100‐hPa tropically averaged temperature difference is larger (i.e., is colder in imposed‐QBOE compared to imposed‐QBOW; Figure ). This suggests, though does not conclusively show, that 100‐hPa QBO‐related temperature anomalies may drive the strengthening of the MJO, as has been proposed and supported by other studies (Hendon & Abhik, ; Martin et al, ; Son et al, ). In imposed‐QBO experiments where the MJO is strong and initialized in Phase 4, there is still a weak but significant MJO response despite the smaller sample size, especially when the MJO is in Phases 6–8 (Figures and ). Differences in other subsets of experiments, such as strong, Phase 2 MJO events, show no significant response (Figure ).…”
Section: Discussionmentioning
confidence: 60%
“…What physical mechanisms may control this apparent, albeit small, increase in MJO amplitude? As discussed in section , a key hypothesis supported by both modeling and observational evidence contends that QBO changes to temperatures in the tropopause region play a key role in modulating the MJO (Abhik & Hendon, ; Hendon & Abhik, ; Martin et al, ; Nie & Sobel, ). The spread in Figure f further demonstrates that, in our I‐QBOE and I‐QBOW experiments, despite starting with the same initial conditions the model maintains the imposed‐QBO temperature signals differently across different runs.…”
Section: Resultsmentioning
confidence: 99%
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“…Easterly QBO phases favor a more active MJO over the Maritime Continent than westerly QBO phases (Densmore et al, ), which may explain the propagation of the MJO further into the east Pacific. Easterly QBO phases also induce anomalously cold temperature at the tropical tropopause, which could encourage more vigorous convection and thereby a healthier MJO (Martin et al, ). Furthermore, connections between the MJO and the North Pacific storm track are modulated by the QBO, with easterly QBO phases favoring a more longitudinally expansive and intense storm track (Wang et al, ).…”
Section: Introductionmentioning
confidence: 99%