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  1. Links Section In This Post, below the intro. I have been recently asked to start a thread, to talk about weather teleconnections and similar topics. This is often a topic not very well discussed on other weather places, and places like Twitter. We have a number of experts, enthusiasts, and meteorologists, who are knowledgeable in this area. So this is a thread for technical discussion about the teleconnections, etc, as well as a place for questions about these topics. We need to start talking about these climate drivers more, as they are the key to unlocking medium-long term forecasts. We are making a place for technical discussion about these factors away from the main thread/s. So this thread is born. Teleconnections that could be up for discussion are: MJO, AAM/GWO, NAO, RRWT, NP jet, Mountain & Frictional Torques, AO/AAO, ENSO, IOD, AMO, SSTs in general, SOI, QBO, the Stratosphere, etc. Feel free to talk about related topics, but stick to this general topic. I encourage all posters to discuss and pose questions relating to the topic, and keep it a relaxed atmosphere. Any questions, just PM me or comment here. Hope we can make this work Links Section ERSL Link, Up to 24 hours behind. GWO 90 day Victor Gensini Site. http://atlas.niu.edu/gwo/ Features Total AAM, Bias Corrected Rel AAM GEFS, CFS GWO Forecast. He stated he is soon to add torque products. Nick Schraldi GWO Site http://www.atmos.albany.edu/student/nschiral/gwo.html Non-Bias Corrected GEFS GWO forecast. Michael Ventrice http://mikeventrice.weebly.com/hovmollers.html Hovmoller from MV, to help spot AAM trends and patterns. GEFS. Carl Schreck https://ncics.org/portfolio/monitor/mjo/ More Hovmollers and other tropical charts to spot trends in the AAM. CFS forecast. NPJ Phase Diagrams/Albany http://www.atmos.albany.edu/facstaff/awinters/realtime/Deterministic_NPJPD.php Shows a GEFS forecast and observation of NP jetstream, which is largely controlled by the AAM. From @Bring Back 1962-63: Since the service provided through WDT was withdrawn there was a gap in this vitally important data. I've been in touch with Ed Berry, who along with Dr Klaus Weickmann (who retired 2 years ago) developed the GSDM (I posted on that on both the 33 and NetWx forums with Ed's excellent presentation earlier this year) and he told me that a friend of his still processes this data. He has kindly provided a link to that site plus the access user name and password: http://gsdmsolutions.com/~gsdm/clim/aam.rean.shtml un = gsdm01 pw = gu3st#1 That will take you to this page where you'll find a lot more than just the ex WDT data: Monitoring of Global Atmospheric Angular Momentum (AAM) Budget NCEP-NCAR Reanalysis DAILY DATA Vertically-integrated 5-day running mean: 1968-1997 Climatology Plots show some of the features: MJO, SUB-MONTHLY, & RAPID TRANSITIONS. ( Plots contain data through (MM/DD/YYYY) = 09/26/2018 ) PLOTS LATEST 90 DAYS LATEST 90 DAYS w/ Seasonal Cycle CURRENT YEAR CURRENT YEAR w/ Seasonal Cycle Data Files AAM data file (Updated: Friday, 28-Sep-2018 08:35:48 CDT) AAM 1-21 data file (Updated: Friday, 28-Sep-2018 08:35:50 CDT) TAUC data file (Updated: Friday, 28-Sep-2018 08:35:57 CDT) TAUF data file (Updated: Friday, 28-Sep-2018 08:35:57 CDT) TAUG data file (Updated: Friday, 28-Sep-2018 08:35:57 CDT) TAUM data file (Updated: Friday, 28-Sep-2018 08:35:57 CDT) TEND data file (Updated: Friday, 28-Sep-2018 08:36:00 CDT) TEND (1-21) data file (Updated: Friday, 28-Sep-2018 08:36:02 CDT) TRANSP data file (Updated: Friday, 28-Sep-2018 08:36:00 CDT) MONTHLY DATA Vertically-integrated: 1968-1997 Climatology Plots show some of the features: ENSO, QBO, & TRENDS. ( Plots contain data through 08/31/2018 ) PLOTS 1958-PRESENT: Total Fields 1958-PRESENT: Anomaly Fields MJO Composites: http://www.atmos.albany.edu/facstaff/roundy/waves/rmmcyc/index200reg.html
  2. Bring Back 1962-63

    Studies of atmospheric angular momentum

    Studies of atmospheric angular momentum Authors: NOAA, Climate Diagnostics Center, Science Review Published: 25th/26th July, 2001 Chapter 4: Empirical and Process Studies Introduction to chapter 4, part 3: Atmospheric angular momentum (AAM) provides a convenient framework to study the role of mountains, surface wind stresses and various transport mechanisms in variability ranging from intraseasonal to interdecadal and beyond. Quantitative studies are feasible with current global assimilated datasets which show a good budget balance for global integrals, intraseasonal variations and during northern winter/spring. The budgets get much worse when gravity wave drag is included, if zonal integrals are considered or during summer/fall seasons. AAM is useful as an index of the large scale zonal flow since it is highly correlated with independent length-of-day measurements and with phenomena such as the QBO, ENSO, the MJO and possibly global warming. CDC scientists have examined several aspects of AAM variability, including: the link to MJO tropical convection, a linear model of global AAM and its torques, the global AAM budget imbalances due to gravity wave drag, the forcing for the semiannual seasonal component of AAM and the AAM response to global warming in an ensemble of coupled ocean-atmosphere model runs. CDC also monitors in real time the complete vertically integrated budget as part of its web-based maproom activities and distributes AAM and torque data to other researchers. Link to full paper: https://www.esrl.noaa.gov/psd/psd1/review/Chap04/sec3_body.html Link to Introduction to Chapter 4: https://www.esrl.noaa.gov/psd/psd1/review/Chap04/index.html Link to full Science Review: https://www.esrl.noaa.gov/psd/psd1/review/SciRev.pdf
  3. MJO Phase Speed and Blocking - Presentation A presentation at the AMS 97th Annual meeting: Conference on “Fifth Symposium on Prediction of the MJO: Processes, Prediction and Impact” held at Washington State Convention Center between 23rd and 25th January, 2017 Presenters: Paul E. Roundy and R. M. Setzenfand Presentation Date: 23rd January, 2017 Presentation Summary: The phase speed of the MJO might be regulated by many different factors. Previous works have suggested that moist processes govern the phase speed. Yet, convection and rainfall tend to be less intense in MJO events propagating more slowly than 5 ms−1 than for MJO events moving at around 5 ms−1. This presentation reflects on a dynamical feedback that might influence MJO phase speed: Rossby wave breaking and blocking. A wavelet filter is applied to extract time series characterized by selected zonal wavenumbers and frequencies at select equatorial base longitudes. Results show that anomalies of active convection characterized by wavenumber 2 (the dominant scale of MJO convection over the warm pool) are associated with meridional potential vorticity (PV) gradients across the tropics to the east of the active convection that are near climatology for events moving east at 5 ms−1. These gradients are much weaker for slower events. The slowest phase speed events have almost no meridional PV gradients across the tropics between the mean latitudes of the subtropical jet streams, suggesting that jet exit regions occur immediately east of the deep convection, dumping mass in the upper troposphere over the region of suppressed convection. In the absence of PV gradients, synoptic to planetary scale waves moving into that environment break or cease to propagate linearly. This analysis is part of broader study of the association of the global atmospheric circulation with the phase speed of MJO convection. Link to conference video presentation (15 minutes): https://ams.confex.com/ams/97Annual/videogateway.cgi/id/37087?recordingid=37087&uniqueid=Paper302240&entry_password=987428 Link to full conference agenda: https://ams.confex.com/ams/97Annual/webprogram/5MJO.html Credit goes to Eric @Webberweather for finding this presentation - thank you.
  4. Circulation Response to Fast and Slow MJO Episodes Authors: Priyanka Yadav and David M. Straus Published: 6th April, 2017 Abstract: Fast and slow Madden–Julian oscillation (MJO) episodes have been identified from 850- and 200-hPa zonal wind and outgoing longwave radiation (OLR) for 32 winters (16 October–17 March) 1980/81–2011/12. For 26 fast cases the OLR took no more than 10 days to propagate from phase 3 (convection over the Indian Ocean) to phase 6 (convection over the western Pacific). For 8 slow cases the propagation took at least 20 days. Fast episode composite anomalies of 500-hPa height (Z500) show a developing Rossby wave in the mid-Pacific with downstream propagation through MJO phases 2–4. Changes in the frequency of occurrence of the NAO+ weather regime are modest. This Rossby wave is forced by anomalous cooling over the Maritime Continent during phases 2 and 3 (seen in phase-independent wave activity flux). The upper-level anticyclonic response to phase-3 heating is a secondary source of wave activity. The Z500 slow episode composite response to MJO phases 1 and 2 is an enhanced Aleutian low followed by a North American continental high. Following phase 4 the development of an NAO+ like pattern is seen over the Atlantic, transitioning to a strong NAO− pattern by phase 8. A dramatic increase in frequency of the NAO+ weather regime follows phases 4 and 5, while a strong increase in NAO− regime follows phases 6 and 7. The responses to MJO-related heating and cooling over the Indian and western Pacific Oceans in phases 1–4 provide a source for wave activity propagating to North America, augmented by storm-track anomalies. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-16-0352.1 Credit goes to Eric @Webberweather for finding this paper - thank you.
  5. Observed Changes in the Lifetime and Amplitude of the MJO Associated with Interannual ENSO Sea Surface Temperature Anomalies Authors: Benjamin Pohl and Adrian J. Matthews Published: 1st June, 2007 Abstract: The Madden–Julian oscillation (MJO) is analyzed using the reanalysis zonal wind– and satellite outgoing longwave radiation–based indices of Wheeler and Hendon for the 1974–2005 period. The average lifetime of the MJO events varies with season (36 days for events whose central date occurs in December, and 48 days for events in September). The lifetime of the MJO in the equinoctial seasons (March–May and October–December) is also dependent on the state of El Niño–Southern Oscillation (ENSO). During October–December it is only 32 days under El Niño conditions, increasing to 48 days under La Niña conditions, with similar values in northern spring. This difference is due to faster eastward propagation of the MJO convective anomalies through the Maritime Continent and western Pacific during El Niño, consistent with theoretical arguments concerning equatorial wave speeds. The analysis is extended back to 1950 by using an alternative definition of the MJO based on just the zonal wind component of the Wheeler and Hendon indices. A rupture in the amplitude of the MJO is found in 1975, which is at the same time as the well-known rupture in the ENSO time series that has been associated with the Pacific decadal oscillation. The mean amplitude of the MJO is 16% larger in the postrupture (1976–2005) compared to the prerupture (1950–75) period. Before the 1975 rupture, the amplitude of the MJO is maximum (minimum) under El Niño (La Niña) conditions during northern winter, and minimum (maximum) under El Niño (La Niña) conditions during northern summer. After the rupture, this relationship disappears. When the MJO–ENSO relationship is analyzed using all-year-round data, or a shorter dataset (as in some previous studies), no relationship is found. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/JCLI4230.1 Credit goes to Eric @Webberweather for finding this paper - thank you.
  6. Modulation of equatorial Pacific westerly/easterly wind events by the MJO and convectively‑coupled Rossby waves Authors: Martin Puy, J. Vialard, M. Lengaigne and E. Guilyardi Published: 16th June, 2015 Abstract: Synoptic wind events in the equatorial Pacific strongly influence the El Niño/Southern Oscillation (ENSO) evolution. This paper characterizes the spatio-temporal distribution of Easterly (EWEs) and Westerly Wind Events (WWEs) and quantifies their relationship with intraseasonal and interannual large-scale climate variability. We unambiguously demonstrate that the Madden–Julian Oscillation (MJO) and Convectively-coupled Rossby Waves (CRW) modulate both WWEs and EWEs occurrence probability. 86 % of WWEs occur within convective MJO and/or CRW phases and 83 % of EWEs occur within the suppressed phase of MJO and/or CRW. 41 % of WWEs and 26 % of EWEs are in particular associated with the combined occurrence of a CRW/MJO, far more than what would be expected from a random distribution (3 %). Wind events embedded within MJO phases also have a stronger impact on the ocean, due to a tendency to have a larger amplitude, zonal extent and longer duration. These findings are robust irrespective of the wind events and MJO/CRW detection methods. While WWEs and EWEs behave rather symmetrically with respect to MJO/CRW activity, the impact of ENSO on wind events is asymmetrical. The WWEs occurrence probability indeed increases when the warm pool is displaced eastward during El Niño events, an increase that can partly be related to interannual modulation of the MJO/CRW activity in the western Pacific. On the other hand, the EWEs modulation by ENSO is less robust, and strongly depends on the wind event detection method. The consequences of these results for ENSO predictability are discussed. Link to full guide: https://www.researchgate.net/profile/Eric_Guilyardi/publication/278682276_Modulation_of_equatorial_Pacific_westerlyeasterly_wind_events_by_the_Madden-Julian_oscillation_and_convectively-coupled_Rossby_waves/links/568d30f608aef987e565dcb5.pdf
  7. Bring Back 1962-63

    A Review of ENSO Theories

    A Review of ENSO Theories Authors: Chunzai Wang Published: 10th October, 2018 Abstract: The ENSO occurrence can be usually explained by two views of (1) a self-sustained oscillatory mode and (2) a stable mode interacting with high-frequency forcing such as westerly wind bursts and Madden-Julian Oscillation events. The positive ocean-atmosphere feedback in the tropical Pacific hypothesized by Bjerknes leads ENSO event to a mature phase. After ENSO event matures, negative feedbacks are needed to cease ENSO anomaly growth. Four negative feedbacks have been proposed: (1) reflected Kelvin waves at the ocean western boundary, (2) a discharge process due to Sverdrup transport, (3) western Pacific wind-forced Kelvin waves, and (4) anomalous zonal advections and wave reflection at the ocean eastern boundary. These four ENSO mechanisms are respectively called as the delayed oscillator, the recharge-discharge oscillator, the western Pacific oscillator and the advective-reflective oscillator. The unified oscillator is developed by including all ENSO mechanisms, i.e., all of four ENSO oscillators are special cases of the unified oscillator. The tropical Pacific Ocean and atmosphere interaction can also induce coupled slow westward and eastward propagating modes. An advantage of the coupled slow modes is that they can be used to explain the propagating property of interannual anomalies, whereas the oscillatory modes produce a standing oscillation. The research community has recently paid attention to different types of ENSO events by focusing on the central Pacific El Niño. All of the ENSO mechanisms may work for the central Pacific El Niño events, with an addition that the central Pacific El Niño may be related to forcing or processes in the extratropical Pacific. Link to full paper: This very recent paper is behind a paywall but I found this link to the pre-submission version: https://www.researchgate.net/profile/Chunzai_Wang/publication/327715816_A_Review_of_ENSO_Theories/links/5ba05a9592851ca9ed11bdcc/A-Review-of-ENSO-Theories.pdf Once in the Researchgate site, you'll find a personally downloadable to your own browser pdf file.
  8. Atmospheric and surface variations during westerly wind bursts in the tropical western Pacific Authors: John Fasullo and Peter J. Webster Published: 6th April 1999 Abstract: An analysis is made of variations in both the surface energy balance and the regional atmospheric dynamic and thermal structure during 44 westerly wind bursts (WWBs) in the western equatorial Pacific Ocean from 1979 to 1995. The study assesses winds, convective available potential energy, cloud properties, precipitation, surface temperature, and surface heat flux while distinguishing between brief (5–25 day periodicity) and sustained (30–90 day) WWBs. Datasets used in the study include fields from the NCEP/NCAR and ECMWF re‐analyses, and satellite retrievals of clouds (ISCPP), precipitation (MSU), moisture (TOVS), and surface solar flux. Both brief and sustained WWBs, by definition, experience strong low‐level westerly winds that typically induce an increased surface latent‐heat flux of approximately 30 W m−2. Enhanced cloud thickness, precipitation, and upper tropospheric easterly wind anomalies accompany surface westerly winds, though maxima in winds lag those in clouds and precipitation by about one day for brief WWBs and four days for sustained events. WWBs of both types experience strong seasonality, occurring frequently in all seasons except boreal summer. Important distinctions between brief and sustained WWBs can also be made. Westerly anomalies typically extend above 200 hPa during brief WWBs but are generally confined to the lower troposphere (below 400 hPa) for sustained events. Sustained WWBs are also preceded by a quiescent period of reduced cloud thickness and surface winds that is accompanied by strong incident solar flux. Convective instability, as judged by a variety of techniques, increases by approximately 30% during this quiescent period. Brief WWBs do not include the precursory surface warming or convective destabilization of sustained WWBs. Notwithstanding the warming episodes before the events, sustained WWBs are associated with a net surface cooling approximately 40% larger than brief WWBs. The relationship between brief and sustained WWBs and the phase of the Madden‐Julian Oscillation (MJO) (as judged from outgoing long‐wave radiation) is also examined. Results support the classification of events as ‘brief’ and ‘sustained’ as used in this study, with brief WWBs occurring frequently during both wet and dry phases of the MJO, while sustained WWBs occur uniquely during the MJO wet phase. The association of brief and sustained WWBs with the MJO is shown to be independent of the El Niiio Southern Oscillation phase. It is therefore proposed that some, but not all, WWBs may be viewed as the surface signature of the MJO and that the mechanisms responsible for the MJO play an integral role in the formation and sustenance of sustained WWBs. Link to full paper: http://webster.eas.gatech.edu/Papers/Webster2000g.pdf
  9. Assessing the Relationship between MJO and Equatorial Pacific WWBs in Observations and CMIP5 Models Authors: Jie Feng and Tao Lian Published: 13th July, 2018 Abstract: This study evaluates the relationship between the Madden–Julian Oscillation (MJO) and the occurrence of equatorial Pacific Westerly Wind Bursts (WWBs). During the convective MJO phase, anomalous surface westerlies prevail in and west of the convective MJO center, providing favorable conditions for WWBs. Compared with the probability of WWBs expected under a null hypothesis that WWBs occur randomly, the convective MJO phase almost doubles the probability of a WWB occurring. Nevertheless, only 34.46% of WWBs co-occur with the convective MJO, which is much less than that reported in previous studies. We show that when the MJO and WWBs are defined using the same field with overlapping frequencies, the percentage of WWBs co-occurred with the convective MJO shows a significant increase. However, the higher percentage is simply caused by the fact that the strong WWBs during a convective MJO are more likely to be identified than those during the suppressed and neutral MJO phases. 45.80% of WWBs are found occurred in the full MJO phase (both the convective and suppressed MJO phases), which is slightly higher than that expected based on randomness. Although the full MJO has statistically significant impact on WWBs likelihood, the influence from the full MJO on the tropical Pacific sea surface temperature anomaly is much weaker as compared to that from the WWBs. The relationships between the MJO and WWBs simulated in CMIP5 models are also assessed, and the percentage of WWBs co-occurred with MJO simulated in models is in general less than that in observations. Link to full paper: This recent paper is still behind a paywall on the AMS website but I found the Preliminary Accept pdf version on the Researchgate site (you will need to to click on the download option at the top left of the page and it will appear in your browser or on your device): https://www.researchgate.net/publication/325278475_Assessing_the_Relationship_between_MJO_and_Equatorial_Pacific_WWBs_in_Observations_and_CMIP5_Models
  10. Stratospheric Control of the Madden–Julian Oscillation Author: Lesley J. Gray Published: Nov 2016 Abstract: Interannual variation of seasonal-mean tropical convection over the Indo-Pacific region is primarily controlled by El Niño–Southern Oscillation (ENSO). For example, during El Niño winters, seasonal-mean convection around the Maritime Continent becomes weaker than normal, while that over the central to eastern Pacific is strengthened. Similarly, subseasonal convective activity, which is associated with the Madden–Julian oscillation (MJO), is influenced by ENSO. The MJO activity tends to extend farther eastward to the date line during El Niño winters and contract toward the western Pacific during La Niña winters. However, the overall level of MJO activity across the Maritime Continent does not change much in response to the ENSO. It is shown that the boreal winter MJO amplitude is closely linked with the stratospheric quasi-biennial oscillation (QBO) rather than with ENSO. The MJO activity around the Maritime Continent becomes stronger and more organized during the easterly QBO winters. The QBO-related MJO change explains up to 40% of interannual variation of the boreal winter MJO amplitude. This result suggests that variability of the MJO and the related tropical–extratropical teleconnections can be better understood and predicted by taking not only the tropospheric circulation but also the stratospheric mean state into account. The seasonality of the QBO–MJO link and the possible mechanism are also discussed. Link to full paper: https://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0620.1
  11. Bring Back 1962-63

    A Climatology of Central American Gyres

    A Climatology of Central American Gyres Authors: Philippe P. Papin, Lance F. Bosar, and Ryan D. Torn Published: 2nd May, 2017 Abstract: Central American gyres (CAGs) are large, closed, cyclonic circulations that occur during the rainy season (May–November), which can yield exceptional rainfall leading to catastrophic flooding and large societal impacts. A reanalysis-based climatology of CAGs is developed from an algorithm that distinguishes CAG cases from other systems. This algorithm identified CAG cases based on circulation intensity, a broad radius of maximum winds, and the existence of closed, Earth-relative, cyclonic flow. Based on these criteria, 47 CAG cases were identified from 1980 to 2010, featuring a bimodal distribution of cases with maxima in May–June and September–November. CAG cases are composited into two categories based on their upper-tropospheric PV structure: nonbaroclinic CAGs are more common (N = 42) and characterized by an upper-tropospheric anticyclone, while baroclinic CAGs are less common (N = 5) and characterized by an upper-tropospheric trough. Whereas a nonbaroclinic CAG has anomalous moisture and precipitation surrounding the center, a baroclinic CAG has anomalous moisture and precipitation concentrated east of the center, with these structural differences attributed to their upper-tropospheric PV structure. Both nonbaroclinic and baroclinic CAGs are preceded by anomalous westerly lower-tropospheric flow in the eastern Pacific before their development, which is linked to a climatological reduction in easterly trade winds and is coincident with MJO phases 1, 2, and 8. Extreme precipitation is observed over multiple days in all available CAG cases, most commonly along the Central American coastline and on average over a large fractional area (25%) within 10° of their center. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-16-0411.1
  12. Bring Back 1962-63

    Why do Earth's equatorial waves head east?

    Why do Earth's equatorial waves head east? Authors: Joseph A. Biello and Tudor Dimofte Published: 24th November, 2017 Abstract: Equatorial Kelvin waves occur constantly in Earth's atmosphere and ocean. They constitute an isolated and powerful component of the observed atmospheric wave spectrum (1), whereas oceanic Kelvin waves drive up- and downwelling in the Pacific Ocean thermocline, which affects the El Niño–Southern Oscillation. In the atmosphere, Kelvin waves are initiated by and coupled to convective activity (storm systems), mostly over the Indian and the western Pacific Oceans, whereas in periods of large-scale convective organization, such as the Madden-Julian Oscillation, equatorial Kelvin wave activity is suppressed. On page 1075 of this issue, Delplace et al. (2) attempt to answer the questions of why there are three equatorially confined waves, and why they all have eastward group velocity. They propose a fascinating perspective on the existence of unidirectional, equatorially confined atmospheric waves by developing an analogy with similar phenomena that occur in electronic materials—in particular, in quantum Hall states and topological insulators. Link to full paper: Unfortunately this great looking recent paper is still behind a "Science" Webinar paywall but it should be available on a free to view basis next year and I will provide the pdf link as soon as I can after that. For those who have a subscription, here's the link to the abstract on the "Science" website: http://science.sciencemag.org/content/358/6366/990 I found an image of the cover page:
  13. Bring Back 1962-63

    Kelvin Waves - A Learner's Guide

    Kelvin Waves - A Learner's Guide Authors: B Wang, University of Hawaii, Honolulu, HI, USA Published: Encylopedia of Atmospheric Scieinces, 2002 Introduction: The Kelvin wave is a large-scale wave motion of great practical importance in the Earth’s atmosphere and ocean. Discovered by Sir William Thompson (who later became Lord Kelvin) in 1879, the Kelvin wave is a special type of gravity wave that is affected by the Earth’s rotation and trapped at the Equator or along lateral vertical boundaries such as coastlines or mountain ranges. The existence of the Kelvin wave relies on (a) gravity and stable stratification for sustaining a gravitational oscillation, (b) significant Coriolis acceleration, and (c) the presence of vertical boundaries or the equator. The unique feature of the Kelvin wave is its unidirectional propagation. The Kelvin wave moves equatorward along a western boundary, poleward along an eastern boundary, and cyclonically around a closed boundary (counterclockwise in the Northern Hemisphere and clockwise in the Southern Hemisphere). The wave amplitude is largest at the boundary and decays exponentially with distance from it. At the Equator, Kelvin waves always propagate eastward, reaching their maximum magnitude at the Equator and decaying exponentially with increasing latitude. There are two basic types of Kelvin waves: boundary trapped and equatorially trapped. Each type of Kelvin wave may be further subdivided into surface and internal Kelvin waves. Surface, or barotropic, waves penetrate the entire depth of the fluid. Kelvin waves also appear within the stably stratified ocean and atmosphere, and are called internal, or baroclinic, Kelvin waves. Internal Kelvin waves are often found in a layer with large density gradients; the density gradient acts as an interface that allows the existence of internal gravity waves. Examples of such density gradients are the oceanic thermocline (a layer of large vertical temperature gradient separating a shallow layer of warm surface water about 50–200 m deep and a much deeper layer of cold water below) and the lower edge of an atmospheric inversion, a layer in which temperature increases with height. Like gravity waves, Kelvin waves can also propagate vertically in a continuously stratified geophysical fluid. Atmospheric Kelvin waves play an important role in the adjustment of the tropical atmosphere to convective latent heat release, in the stratospheric quasibiennial oscillation, and in the generation and maintenance of the Madden–Julian Oscillation. Oceanic Kelvin waves play a critical role in tidal motion, in the adjustment of the tropical ocean to wind stress forcing, and in generating and sustaining the El Nin˜o Southern Oscillation. Link to full paper: https://www.soest.hawaii.edu/MET/Faculty/bwang/bw/paper/wang_103.pdf
  14. More Frequent Sudden Stratospheric Warming Events due to Enhanced MJO Forcing Expected in a Warmer Climate Authors: Kang and Tziperman Published: July 2017 Abstract: Sudden stratospheric warming (SSW) events influence the Arctic Oscillation and midlatitude extreme weather. Observations show SSW events to be correlated with certain phases of the Madden–Julian oscil- lation (MJO), but the effect of the MJO on SSW frequency is unknown, and the teleconnection mechanism, its planetary wave propagation path, and time scale are still not completely understood. The Arctic stratosphere response to increased MJO forcing expected in a warmer climate using two models is studied: the compre- hensive Whole Atmosphere Community Climate Model and an idealized dry dynamical core with and without MJO-like forcing. It is shown that the frequency of SSW events increases significantly in response to stronger MJO forcing, also affecting the averaged polar cap temperature. Two teleconnection mechanisms are identified: a direct propagation of MJO-forced transient waves to the Arctic stratosphere and a nonlinear enhancement of stationary waves by the MJO-forced transient waves. The MJO-forced waves propagate poleward in the lower stratosphere and upper troposphere and then upward. The cleaner results of the idealized model allow identifying the propagating signal and suggest a horizontal propagation time scale of 10–20 days, followed by additional time for upward propagation within the Arctic stratosphere, although there are significant uncertainties involved. Given that the MJO is predicted to be stronger in a warmer climate, these results suggest that SSW events may become more frequent, with possible implications on tropospheric high-latitude weather. However, the effect of an actual warming scenario on SSW frequency involves additional effects besides a strengthening of the MJO, requiring further investigation. Link to full paper: https://www.seas.harvard.edu/climate/eli/reprints/Kang-Tziperman-2017.pdf
  15. Effect of Madden–Julian Oscillation Occurrence Frequency on the Interannual Variability of Northern Hemisphere Stratospheric Wave Activity in Winter Authors: Feiyang Wang, Wenshou Tian, Fei Xie, Jiankai Zhang and Yuanyuan Han Published: 12th March, 2018 (on line: 1st June, 2018) Abstract: This study uses reanalysis datasets and numerical experiments to investigate the influence of the occurrence frequency of the individual phases of the Madden–Julian oscillation (MJO) on the interannual variability of stratospheric wave activity in the middle and high latitudes of the Northern Hemisphere during boreal winter [November–February (NDJF)]. Our analysis reveals that the occurrence frequency of MJO phase 4 in winter is significantly positively correlated with the interannual variability of the Eliassen–Palm (E–P) flux divergence anomalies in the northern extratropical stratosphere; that is, higher (lower) occurrence frequency of MJO phase 4 corresponds to weaker (stronger) upward wave fluxes and increased (decreased) E–P flux divergence anomalies in the middle and upper stratosphere at mid-to-high latitudes, which implies depressed (enhanced) wave activity accompanied by a stronger (weaker) polar vortex in that region. The convection anomalies over the Maritime Continent related to MJO phase 4 excite a Rossby wave train that propagates poleward to middle and high latitudes, and is in antiphase with the climatological stationary waves of wavenumber 1 at middle and high latitudes. As the spatial distribution of the convection anomalies during MJO phase 7 has an almost opposite, but weaker, pattern to that during MJO phase 4, the occurrence frequency of MJO phase 7 has an opposite and weaker effect on the northern extratropical stratosphere to MJO phase 4. However, the other MJO phases of 1, 2, 3, 5, 6 and 8, cannot significantly influence the northern extratropical stratosphere because the wave responses in these phases are neither totally in nor out of phase with the background stationary wavenumber 1. Link to full paper: This excellent very recent paper was behind an AMS paywall but I found a copy which I was able to download onto a personal pdf file and then convert to a word document and I copy the full paper below (with charts and diagrams added separately): ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Effect of Madden–Julian Oscillation Occurrence Frequency on the Interannual Variability of Northern Hemisphere Stratospheric Wave Activity in Winter FEIYANG WANG AND WENSHOU TIAN Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Science, Lanzhou University, Lanzhou, China FEI XIE College of Global Change and Earth System Science, Beijing Normal University, Beijing, China JIANKAI ZHANG AND YUANYUAN HAN Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Science, Lanzhou University, Lanzhou, China (Manuscript received 17 July 2017, in final form 12 March 2018) ABSTRACT 1. Introduction Planetary wave activity in the extratropical strato- sphere plays an important role in the dynamical coupling between the troposphere and stratosphere (e.g., Kuroda and Kodera 1999; Perlwitz and Graf 2001; Kushner and Polvani 2004; Perlwitz and Harnik 2004). Previous studies have found that stratospheric wave activity has increased in the early winter but decreased significantly in the late winter during past decades (e.g., Newman and Nash 2000; Randel et al. 2002; Hu and Tung 2003). As wave activity in the extratropical stratosphere is a precursor to strato- spheric events, the stratospheric polar vortex and Brewer–Dobson circulation (BDC) evolve with the wave activity (Polvani and Waugh 2004; Butchart et al. 2006; Garcia and Randel 2008; Garfinkel et al. 2015). The changing Arctic polar vortex and BDC can, in turn, in- fluence the tropospheric weather and climate across a wide range of time scales (Thompson and Wallace 2001; Karpechko and Manzini 2012; Xie et al. 2016; Zhang et al. 2016). It is, therefore, important to understand the factors that control the variability of the wave activity in the northern extratropical stratosphere. The stratospheric planetary wave activity shows pro- nounced interannual variability in winter in the Northern Hemisphere. It is well known that the interannual vari- ability of the extratropical stratosphere is related to tropical variability, such as the quasi-biennial oscillation (QBO; Holton and Tan 1980, 1982; Garfinkel et al. 2012a; Lu et al. 2014) and El Niño–Southern Oscillation (ENSO; Calvo Fernández et al. 2004, 2009; Manzini et al. 2006; Camp and Tung 2007; Garfinkel and Hartmann 2008; Cagnazzo and Manzini 2009; Cagnazzo et al. 2009; Ren et al. 2012; Xie et al. 2012; Zhang et al. 2015a,b). Strato- spheric planetary waves originate predominately in the troposphere, and their variations are caused by variability in two main factors: wave propagation from the tropo- sphere into the stratosphere, and tropospheric wave ac- tivity intensity. Wave propagation from the troposphere into the stratosphere can be affected by the QBO. The QBO affects extratropical wave propagation in two ways: the first is the stratospheric waveguide change due to the modulation by the QBO of the latitudinal location of the zero-wind line (i.e., the critical line for stationary waves) in the subtropics (Holton and Tan 1980, 1982), and the other is changes to planetary wave propagation and breaking caused by the effect of the QBO-induced meridional circulation on the refractive index (e.g., Garfinkel et al. 2012a; Lu et al. 2014). Variations in the intensity of tropospheric wave activity are mainly driven by tropical processes, for example, by ENSO. Warm ENSO events induce a deepening of the winter Aleutian low via the Pacific–North American (PNA) pattern, leading to an increase in wavenumber-1 eddies and a weakened vortex. However, the extratropical atmo- spheric circulation is not only influenced by ENSO and QBO, but also the Madden–Julian oscillation (MJO). The MJO is the dominant mode of intraseasonal variability in the tropical atmosphere (Madden and Julian 1971, 1972, 1994). A typical MJO event begins with a convective disturbance over the far equatorial western Indian Ocean and then intensifies and propa- gates eastward slowly (;5m s21) to the equatorial cen- tral Pacific Ocean. An MJO can be divided into eight phases as the convection center propagates. Previous studies have shown that these intraseasonal anomalies of moist deep convection in the tropics influence the teleconnection patterns over the middle and high lati- tudes, such as the PNA pattern (e.g., Matthews et al. 2004; Mori and Watanabe 2008; Johnson and Feldstein 2010), the North Atlantic Oscillation (NAO; e.g., Cassou 2008; Lin et al. 2009), and the Arctic Oscillation (AO; e.g., Zhou and Miller 2005; L’Heureux and Higgins 2008). Moreover, Lin et al. (2015) have also demonstrated that the seasonal mean convective activity related to MJO phases 3–5 is a possible driver of the seasonal mean NAO variability in boreal winter. Ac- cording to the theoretical studies of Matsuno (1966) and Gill (1980), the coherence between tropical and extra- tropical responses triggered by MJO-related convection is a consequence of Rossby wave trains that extend eastward and poleward across the middle and high lat- itudes. A model-based study by Seo and Son (2012) suggested that the anomalous tropical heating related to MJO phase 3 results in a Rossby wave train traveling north from the tropics into the northern Pacific and North America, and then turning south toward the equatorial African continent. The spatial structure of such a Rossby wave train is similar to that of the PNA pattern. Furthermore, Yoo et al. (2011, 2012) showed that the surface air temperature in the Arctic is also linked to the tropical MJO through the poleward propagation of wave trains. In addition, the ozone transport between the upper troposphere and lower stratosphere over the northern extratropics and Arctic is also affected by the MJO-related teleconnection (Li et al. 2013). The above studies illustrate that the MJO is able to influence wave activity in the northern extra- tropical troposphere. However, the connection between the MJO and wave activity in the northern extratropical stratosphere has received relatively little attention. Newman and Sardeshmukh (2008) have shown a link between tropical diabatic heating on intraseasonal time scales and the polar vortex. Garfinkel et al. (2012b) found a clear correlation between wave activity in the extratropical stratosphere and the MJO. They suggested that Northern Hemisphere sudden stratospheric warm- ing (SSW) events tend to follow certain MJO phases with a delay of a few days. Liu et al. (2014) investigated the connection between the equatorial MJO and dif- ferent types of the Northern Hemisphere midwinter major SSWs. Subsequently, Garfinkel et al. (2014) pointed out more clearly that MJO phase 7, in which convective anomalies propagate into the tropical central Pacific, leads to a North Pacific low, more heat flux in the troposphere, and a weakened vortex, whereas MJO phase 3 leads to the opposite effects. More recently, Schwartz and Garfinkel (2017) found that slightly more than half of SSW events follow MJO phases 6 and 7. However, these studies focused solely on the relation- ship between these two processes over intraseasonal time scales. The question that arises here is the follow- ing: Can the MJO influence the interannual variability of Northern Hemisphere stratospheric wave activity? Even though the MJO operates over intraseasonal time scales, the occurrence frequency of the individual phases of the MJO actually shows year-to-year variability. FIG. 1. Composite OLR (Wm22) anomalies during the eight MJO phases in boreal winter (NDJF). Daily OLR data for the period 1979–2013 were obtained from the CDC (NOAA) and the MJO phases were defined using the real-time multivariate MJO (RMM) index. Only days with MJO amplitude greater than 1.0 were used. OLR anomalies were calculated by removing the daily seasonal cycle and then applying a 100-day high-pass digital filter to the daily time series. The purpose of this paper is to investigate whether the in- terannual variability of the occurrence frequency of the individual phases of the MJO can significantly affect Northern Hemisphere stratospheric wave activity. The remainder of this paper is organized as follows. Section 2 introduces the datasets, methods, and model. Section 3 demonstrates the statistical relationship be- tween the interannual variability of the occurrence fre- quency of the individual phases of the MJO and wave activity in the northern extratropical stratosphere, and the associated mechanism is analyzed in section 4. Fi- nally, we present our conclusions in section 5. 2. Data, methods, and model Interpolated (2.58 longitude 3 2.58 latitude) daily mean outgoing longwave radiation (OLR) data from 1979 to 2013 were obtained from the Climate Diagnostic Center (CDC) of the National Oceanic and Atmospheric Ad- ministration (NOAA). Note that the analysis in this study is limited to the period 1979–2013, corresponding to the availability of the OLR data. The OLR can serve as a proxy for deep convection in the tropics, with lower OLR values corresponding to enhanced convective activity. To identify MJO events, the daily multivariate MJO index (Wheeler and Hendon 2004), which characterizes the state of the MJO in terms of its amplitude and phase, was obtained from the Australian Bureau of Meteorology (online at http://www.bom.gov.au/climate/mjo/). This MJO index consists of the principal components of the leading combined empirical orthogonal functions (EOFs) of the 200- and 850-hPa zonal wind and OLR averaged over the latitude band between 158S and 158N. Based on the index, an MJO cycle (typically ;40– 60 days) is divided into eight phases. The MJO is con- sidered as being active when the amplitude of the MJO index exceeds 1.0. Figure 1 shows the composited OLR anomalies during the eight MJO phases. The original OLR MJO index (OOMI), which is obtained online from the NOAA/Earth System Research Laboratory (online at https://www.esrl.noaa.gov/psd/mjo/mjoindex/oomi.1x.txt), was also used to verify the results in this study. The meteorological fields analyzed in this study were obtained from the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research(NCAR) reanalysis dataset (Kalnay et al. 1996). The dataset contains daily averages of variables on a 2.58 3 2.58 grid at 17 vertical pressure levels ex- tending from 1000 to 10 hPa, with 6 levels in the strato- sphere (100, 70, 50, 30, 20, and 10 hPa). The reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA- Interim; Dee et al. 2011) were also used to verify the results in this study, and were obtained as daily mean fields at 37 discrete pressure levels, on a 18 3 18 horizontal grid. We used wave activity analysis to investigate the en- ergy propagation of stationary Rossby waves. The wave activity flux is parallel to the group velocity of stationary Rossby waves, making it a useful indicator for identify- ing the propagation direction and source of stationary atmospheric Rossby waves. To assess the influence of MJO-related processes on wave activity in the extra- tropical stratosphere, the quasigeostrophic version of the E–P flux divergence was calculated using the NCEP– NCAR daily fields based on the original definition as follows (Edmon et al. 1980) Here p is the pressure; a is the radius of Earth; u is the latitude; f is the Coriolis parameter; u is the potential temperature; and u and y are the zonal and meridional components of the wind, respectively. Eddy flux terms are computed from the zonal anomalies for each day. The E–P fluxes include the wave momentum flux and wave heat flux. The E–P flux divergence reflects the eddy forcing on the zonal mean flow, which can serve as a measure of the wave activity, and a negative (pos- itive) E–P flux divergence represents easterly (westerly) eddy forcing of the mean flow (Andrews et al. 1987). Rossby wave ray tracing was used to further analyze the trajectory of the stationary Rossby wave train and characterize the impact of the background flow on the propagation of wave energy. This theory-based tech- nique uses a curve that is locally tangential to the group velocity vector, and has been widely used to trace the Rossby wave responses to tropical heating anomalies (Hoskins and Karoly 1981; Hoskins and Ambrizzi 1993), and also in research into atmospheric teleconnection mechanisms (Xu et al. 2013; Sun et al. 2015, 2017; Wu et al. 2016; Zheng et al. 2016). The trajectory of a wave ray can be calculated numerically from the angle of the wave front propagation, which is determined from the ratio of the zonal and meridional group velocities. As the Rossby wave propagation trajectories are closely dependent on the basic state, the Rossby wave rays were calculated here for the seasonal climatological flow using the equations in Li and Li (2012), Li et al. (2015), and Zhao et al. (2015) to delineate the propagation behavior of wave energy associated with the MJO. We used the NCAR Community Earth System Model (CESM), version 1.0.6, which is a global climate model (Hurrell et al. 2013). In particular, our model experiments were carried out using version 4 of the Whole Atmosphere Community Climate Model (WACCM4). WACCM4 also incorporates the Community Atmospheric Model, version 4 (CAM4), and as such includes all of its physical parameterizations (Neale et al. 2013). This improved version of WACCM uses a coupled system of four components: atmosphere, ocean, land, and sea ice (Holland et al. 2012). WACCM4 has a finite volume dynamical core, with 66 vertical levels extending from the ground to 4.5 3 1026 hPa (;145-km geometric altitude), and a vertical resolution of 1.1–1.4 km in the tropical tropopause layer and the lower stratosphere (below a height of 30 km). The simulations presented in this paper are performed at a horizontal resolution of 1.98 3 2.58, and include interactive chemistry (Garcia et al. 2007). More details about WACCM4 are available in Marsh et al. (2013). In this study, all relevant daily data of 34-yr boreal winter [November–February (NDJF)] from 1979 to 2013 were analyzed. For all the fields except for the MJO index, the seasonal cycle was removed, and then a 100- day high-pass digital filter was performed on the daily time series. Then, the seasonal means are constructed by averaging variables over NDJF, resulting in 34 winter fields. Note that an area average over the region 408–908N and 10–100 hPa was applied to the filtered E–P flux di- vergence for calculating the time series of wave activity in the extratropical stratosphere. The high-pass filter was chosen to retain atmospheric variations in intra- seasonal time scale and exclude other factors (e.g., QBO or ENSO) that may contaminate the connection be- tween MJO and wave activity in the extratropical stratosphere. After applying the high-pass filter to the E–P flux divergence time series, the standard deviation of the filtered seasonal mean time series was reduced, but the reduction was no more than half of the standard deviation of the unfiltered time series. 3. The correlation between MJO occurrence frequency and wave activity in the northern extratropical stratosphere Figure 2 shows the time series of the occurrence fre- quency of the eight MJO phases, and the E–P flux divergence anomalies in the northern extratropical stratosphere, during winter (NDJF) from NCEP–NCAR reanalysis data. The occurrence frequency of the in- dividual MJO phases was calculated by summing the occurrence days of each phase during winter in each year. Only the days with MJO amplitude greater than FIG. 2. Time series of the occurrence frequency of the eight MJO phases (day; red lines) and northern extratropical stratospheric E–P flux divergence anomalies (m s21 day21; blue lines) during winter (NDJF) from 1979 to 2013 based on NCEP–NCAR reanalysis data. The occurrence frequency of the individual MJO phases was calculated by summing the occurrence days of each phase during winter in each year. Only days with MJO amplitude greater than 1.0 were included. The time series of E–P flux divergence anomalies was obtained by applying a spatial average over the region 408–908N and 10–100 hPa and a time average in winter, after removing the seasonal cycle and then applying a 100-day high-pass filter to the time series. The correlation coefficient between these two linearly detrended time series is shown in the top-right corner of each panel. One (two) asterisk(s) indicate that the correlation coefficient is significant at the 90% (95%) confidence level based on the Student’s t test. 1.0 were included. A 100-day high-pass filter was ap- plied to the E–P flux divergence anomalies before performing the spatial and time average. After the 100- day high-pass filtering, the variations in the averaged E–P flux divergence anomalies highlight the in- terannual variations in the high-frequency northern extratropical stratospheric wave activity in winter. We found that strong in-phase variability exists between the occurrence frequency of MJO phase 4 and the northern extratropical stratospheric E–P flux di- vergence anomalies, with a correlation coefficient of 0.55 that is significant at the 95% confidence level (Fig. 2g). Note that the occurrence frequency of MJO phase 7 has a relatively large anticorrelation with the E–P flux divergence anomalies (R 5 20.31, significant at the 90% confidence level, Fig. 2f). These results suggest that an increase (decrease) in the occurrence frequency of MJO phase 4 during the boreal winter corresponds to weaker (stronger) wave activity in the northern extratropical stratosphere, and vice versa for MJO phase 7. Note that we also used different MJO amplitude threshold values (1.25 and 1.5) and different periods of high-pass filtering (120 and 80 days) to test the robustness of the link between the occurrence TABLE 1. The left column is the correlation coefficients between the frequency of occurrence of the individual MJO phases and E–P flux divergence anomalies in the extratropical stratosphere for an MJO amplitude threshold of 1.25 and 1.5 and the right column for filtering period of 120 and 80 days. When calculating the correlation coefficients for the MJO amplitude threshold of 1.25 and 1.5, the 100-day high-pass filtering is used. When calculating the correlation coefficients for filtering period of 120 and 80 days, the MJO amplitude threshold value 1.0 is used. The E–P flux divergence is calculated from the NCEP–NCAR reanalysis data. One and two asterisks indicate that the correlation coefficient is significant at the 90% and 95% confidence levels, respectively, based on the Student’s t test. frequency of MJO phases and the northern strato- spheric wave activity found in our study. Table 1 lists the correlation coefficients between the frequency of occurrence of the individual MJO phase and E–P flux divergence anomalies under the choice of different MJO amplitude threshold values and different periods of high-pass filtering. It is apparent that the results are not sensitive to the selections of the MJO amplitude threshold value and the reasonable change in the pe- riod of the filtering. The corresponding results from the ERA-Interim data are well consistent with the corre- lations between the occurrence frequencies of MJO phases 4 and 7 and the northern extratropical strato- spheric wave activity anomalies (Table 2). In addition, previous studies have suggested that some factors, such as QBO, ENSO, North Pacific SST, sub- polar snow cover, or sea ice, can affect northern extra- tropical stratospheric wave activity (e.g., Cohen and Jones 2011; Garfinkel et al. 2012a; Hurwitz et al. 2012; Kim et al. 2014; Chen et al. 2016). The link between the occurrence frequency of MJO phases and high- frequency variability of stratospheric wave activity may be affected by these factors. However, the 100-day high- pass filter performed on the time series in this study eliminate the effects of the signals with time scales lon- ger than 100 days. Meanwhile, we found that this link between the occurrence frequency of MJO phases and variability of wave activity in the northern stratosphere is stable when a multiple linear regression was further applied to remove the effects of the abovementioned TABLE 2. As in Table 1, but for E–P flux divergence from ERA-Interim data. factors on the filtered wave activity of the extratropical stratosphere (not shown). Figure 1 shows that the tropical convection is strength- ened over the Maritime Continent but suppressed over the central Pacific during MJO phase 4. In contrast, the pattern of convection anomalies during MJO phase 7 is approximately opposite to that associated with MJO phase 4. This explains why the occurrence frequencies of MJO phases 4 and 7 are oppositely correlated with the northern extratropical stratospheric wave activity anomalies (Figs. 2g,f). Using the data plotted in Fig. 1, the OLR anomalies spatially averaged over the Maritime Continent (158S–58N, 908–1508E) and equatorial central Pacific (158S–58N, 1608E–1508W) during the eight MJO phases are shown in Fig. 3; the convection anomalies at the center of the OLR anomalies during MJO phase 4 are more intense than those that develop during MJO phase 7. Under these circumstances, we can expect that the correlation coefficient between the occurrence frequency of MJO phase 4 and the E–P flux divergence anomalies (Fig. 2g) is more significant than that between MJO phase 7 and the E–P flux divergence anomalies (Fig. 2f). Note that the intensities of convection anomalies at the center of the OLR anomalies FIG. 3. Composite OLR (Wm22) anomalies spatially averaged over the Maritime Continent (158S–58N, 908–1508E) and equatorial central Pacific (158S–58N, 1608E–1508W) during the eight MJO phases in winter (NDJF). Only days when the MJO amplitude was greater than 1.0 were used. OLR anomalies were calculated by removing the seasonal cycle and then applying a 100-day high-pass digital filter to the daily time series. during MJO phases 5 and 8 are also as large as those during MJO phases 4 and 7, respectively. The difference between the influences of the other MJO phases and these two special phases on wave activity will be discussed in the next section. Garfinkel et al. (2014) showed that the enhanced convection in the tropical central Pacific associated with MJO phase 7 leads to a weakened Arctic polar vortex. Our study shows a similar result, with the increased occurrence frequency of MJO phase 7 corresponding to stronger wave activity in the northern extratropical stratosphere. They also showed that the weakened wave activity corresponds to suppressed convection in the central Pacific related to MJO phase 3; however, we have shown that the increased occurrence frequency of MJO phase 4 is related to weaker wave activity in the extratropical stratosphere. These differences may be caused by the different time scales considered by these two studies. Garfinkel et al. (2014) focused on the effect of one MJO phase on extratropical circulation with an intraseasonal time scale, whereas this study investigates the variability on interannual time scales of the link between the occurrence frequency of MJO phase and the northern stratospheric wave activity. The correlation coefficients between the E–P flux divergence anomalies and the occurrence frequency of MJO phases 1, 2, 3, 5, 6, and 8 are small and not significant (Figs. 2a–e,h), suggesting that the connection at interannual time scales between the occurrence frequencies of these MJO phases and wave activity is weak. A transient experiment (E1) is performed with WACCM4 to further confirm the above correlation, using natural and anthropogenic external forcings, including spectrally resolved solar variability (Lean et al. 2005), time varying greenhouse gases (GHGs) (from scenario A1B of IPCC 2001), volcanic aerosols [from the Stratospheric Processes and their Role in Climate (SPARC) Chemistry Climate Model Validation (CCMVal) REF-B2 scenario recommendations], and a nudged QBO (the time series in CESM is determined from the observed climatology over the period 1955– 2005). E1 is a historical simulation integrated over the period 1955–2005. All the forcing data used in this study are available from the CESM model input data repository. Note that previous studies have pointed out that the simulated MJO strength in WACCM is underestimated (Inness et al. 2003; Zhang et al. 2006; Subramanian et al. 2011; Liu et al. 2015; Yang et al. 2017; Kang and Tziperman 2017). However, these studies also pointed out that the CAM-based WACCM, like most atmospheric general circulation models, can reproduce the eastward propagating intraseasonal zonal winds and OLR in the tropical Indian and Pacific Oceans and the responses to MJO in the troposphere and stratosphere. These previous studies indicated that WACCM has the ability to simulate MJO activity, but the simulated intensity of MJO activity is relative weaker than the observation. The results show that the correlation between the observed occurrence frequencies of the eight MJO phases and the northern extratropical stratospheric wave activity anomalies (Fig. 2) is well simulated by the WACCM4 model (Fig. 4) for the period 1960–2005 (the first 5 years are for the spinup period). That is, the northern extratropical stratospheric E–P flux divergence anomalies have the strongest correlation with the occurrence frequency of MJO phase 4 (Fig. 4g) and are anticorrelated with MJO phase 7 (Fig. 4f). To obtain more evidence of the potential influence of MJO phases 4 and 7 on the northern winter extra tropical stratosphere, we defined MJO phases 4 and 7 occurrence frequency indices (Fig. 5). These indices were calculated by removing the mean from the occurrence frequency time series of the MJO phases 4 and 7 in winter (the red lines in Figs. 2g,f). A positive value of the index indicates a high frequency year for MJO phase 4 or 7, whereas a negative value indicates a low frequency year. Figure 5 shows the interannual variability of the indices of MJO phases 4 and 7. It is interesting that MJO phase 4 has a low occurrence frequency in the 1980s but a high occurrence frequency in the 1990s, while the variation of MJO phase 7 is generally opposite to that of MJO phase 4. These two time series show a negative correlation (R 5 20.41, significant at the 95% confidence level). This interesting phenomenon deserves future investigation. The composite anomalies of the E–P flux, E–P flux divergence, and zonal mean temperature from the NCEP–NCAR reanalysis data for high and low occurrence frequency years of MJO phases 4 and 7 during winter for the period 1979–2013 in the northern extratropical stratosphere are shown in Fig. 6. In winters with a high occurrence frequency of MJO phase 4 (Fig. 6a), the weakened upward wave fluxes and stronger E–P flux divergence anomalies in the middle and upper stratosphere at middle and high latitudes imply depressed wave activity, and this is accompanied by negative temperature anomalies in the same region. Conversely, in winters with a low occurrence frequency of MJO phase 4 (Fig. 6b), the enhanced upward wave fluxes and stronger E–P flux convergence imply enhanced wave activity and positive temperature anomalies. As expected, the changes in upward wave fluxes, E–P flux divergence, and zonal-mean temperature in the middle and upper stratosphere at middle and high latitudes associated with MJO phase 7 are just the opposite FIG. 4. As in Fig. 2, but from the WACCM4 experiment (E1). of those associated with MJO phase 4 (Figs. 6c,d). Note that the modulation of the E–P flux during MJO phase 4 is more noticeable than that during MJO phase 7, which is consistent with the correlation analysis (Figs. 2g,f). 4. Mechanism by which the MJO affects the northern extratropical stratosphere It has been demonstrated that tropical forcing can influence the stratospheric polar vortex by modulating the PNA teleconnection pattern in the Northern Hemisphere (Garfinkel and Hartmann 2008; Xie et al. 2012). Subsequently, the wave trains in the upper troposphere can enhance planetary wave propagation into the subpolar stratosphere, which weakens the stratospheric polar vortex. Further investigation is required as to whether the anomalies in the stratospheric circulation and temperature associated with high and low occurrence-frequency years of MJO phases 4 and 7 are also tied to teleconnection pattern and corresponding wave activity in the upper troposphere. To illuminate the connection between tropical MJO phases 4 and 7 and northern extratropical stratospheric wave activity, Fig. 7 shows the geopotential height anomalies at 200 hPa during the high and low occurrence frequency years of MJO phases 4 and 7. The geopotential height anomalies were again calculated by removing the seasonal cycle and then applying a 100 day high pass digital filter to the daily data. As suggested by Seo and Son (2012), anomalous tropical heating related to the MJO results in the Rossby wave train traveling north from the forcing region to the northern Pacific and North America, then turning south toward the equatorial African continent. Figures 7a and 7b show opposite pattern of geopotential height anomalies in the high and low occurrence frequency years of MJO phase 4. This pattern resembles a Rossby wave train traveling north toward the northern Pacific and North America, and FIG. 5. MJO phases (a) 4 and (b) 7 occurrence-frequency indices. The indices were calculated by removing the mean from the occurrence-frequency time series of the MJO phases 4 and 7 in winter (please refer to Fig. 2). then turning south toward the African continent. The spatial structure of the Rossby wave train is similar to that in the PNA pattern. Figures 7c and 7d are the same as in Figs. 7a and 7b, but for MJO phase 7. The pattern of geopotential height anomalies in years with high and low occurrence frequency of MJO phase 7 is generally opposite to that of MJO phase 4. As the intensity of the convection anomalies at the center of the OLR anomalies during MJO phase 4 is larger than during MJO phase 7 (Fig. 3), the geopotential height anomalies in MJO phase 7 (Figs. 7c,d) are smaller than in MJO phase 4 (Figs. 7a,b). To examine the horizontal structures of planetary wave anomalies, Fig. 7 also shows the climatological stationary waves of wavenumber 1 accompanied by the geopotential height anomalies. There is a positive (negative) anomaly superimposed on the Aleutian low over the northern Pacific during the high (low) occurrence frequency years of MJO phase 4. This would lead to a weakened (strengthened) tropospheric wave forcing of wavenumber 1. The teleconnections and poleward traveling of Rossby wave in the upper troposphere can, in turn, alter planetary wave propagation into the subpolar stratosphere, where the waves dissipate, decelerating the stratospheric polar vortex (Garfinkel and Hartmann 2008). Combining Figs. 6 and 7, the mechanism by which the MJO affects the northern extratropical stratospheric planetary wave can be summarized as follows: the propagation of tropical Rossby waves to middle and high latitudes is triggered in both the high and low occurrence-frequency years of MJO phase 4. FIG. 6. Latitude–height cross sections of composite E–P flux (vectors; horizontal term: 107m3 s22 and vertical term: 105 Pam2 s22), E–P flux divergence (shaded; ms21 day21), and zonal-mean temperature (contours; K) anomalies during (a),(c) high- and (b),(d) lowoccurrence- frequency years ofMJO phases (a),(b) 4 and (c),(d) 7. Solid contours are positive, dashed contours are negative, and zero contours are thickened. Contour interval for the zonal-mean temperature anomalies is 0.02 K. FIG. 7. Geopotential height (contours; gpm) anomalies during the (a),(c) high- and (b),(d) low-occurrencefrequency years of MJO phases (a),(b) 4 and (c),(d) 7 at 200 hPa associated with winter-averaged stationary waves of wavenumber 1 (shaded) from the NCEP–NCAR reanalysis data. The geopotential height anomalies were also calculated by removing the daily seasonal cycle and then applying a 100-day high-pass digital filter to the daily data. Solid contours are positive, and dashed contours are negative. Contour interval for the geopotential height anomalies is 0.6 gpm. However, the anomalous waves during the high (low) occurrence frequency years of MJO phase 4 (Figs. 7a,b, the geopotential height anomalies) are out of phase (in phase) with the climatological stationary wavenumber 1 in the Northern Hemisphere. This wave interference leads to weakened (strengthened) planetary waves along the polar wave guide during the high (low) frequency periods of MJO phase 4. Under this condition, it is expected that fewer (more) planetary waves propagate vertically into the stratosphere when the occurrence frequency of the MJO phase 4 is high (low). This explains why there is less (more) E–P flux and positive (negative) E–P flux divergence anomalies during the years with high (low) occurrence frequency of MJO phase 4 (Figs. 6a,b). The above processes are reversed for MJO phase 7. We now use Rossby wave ray tracing to further trace the trajectory of the Rossby wave trains described above. The ray paths of waves with wavenumbers 1–3 at 200 hPa generated by the perturbed circulation over the region 208S–208N, 708–1508E in winter are shown in Fig. 8. The wave ray paths represent the climate teleconnections (i.e., the propagation of stationary waves in realistic flows). The method for calculating the wave ray paths and application of the barotropic model are described in detail by Li et al. (2015) and Zhao et al. (2015). We found that some planetary waves generated by the perturbed circulation over this region, where there are strong convection anomalies in MJO phase 4, travel north to the northern Pacific and North America, and then turn south toward the African continent. This suggests the possibility that Rossby waves generated by a convection anomaly in the tropics related to MJO phase 4 may travel along the ray trajectories to the Northern Hemisphere middle and high latitudes. Thus, it can be expected that some wave ray paths are in agreement with the composite patterns of the geopotential height anomalies in Fig. 7. Figure 9 shows the corresponding vertical structures of the MJO-induced planetary waves that propagate into the stratosphere. The geopotential height anomalies in the northern extratropics during the high (low) occurrence-frequency years of MJO phase 4 generally tilt to the west with height and are in the opposite (same) phase as the climatological wavenumber 1, and this generates destructive (constructive) interference between the MJO induced waves and the background stationary waves (Figs. 9a,b). Thus, the weakened (enhanced) wave activity in the northern extratropical stratosphere corresponding to the high (low) occurrence frequency of MJO phase 4 can be expected. This result is associated with anomalous upward wave flux and E–P flux divergence at middle and high latitudes in the Northern Hemisphere middle and upper stratosphere and accompanied by the temperature anomalies during FIG. 8. Ray paths (green lines) at 200 hPa in winter. Black crosses denote wave sources in the region 208S–208N, 708–1508E. Rays with wavenumbers 1–3 are shown. The shading indicates meridional gradient of quasigeostrophic potential vorticity (K kg21ms21). FIG. 9. Longitude–height cross sections of the spatially averaged (458–758N) geopotential height anomalies (contours; gpm) during (a),(c) high- and (b),(d) low-occurrence-frequency years of MJO phases (a),(b) 4 and (c), (d) 7 with winter-averaged stationary waves of wave number 1 (shaded) from the NCEP–NCAR reanalysis data. Solid contours are positive, dashed contours are negative, and zero contours are thickened. Contour interval for the winter seen in Figs. 6a and 6b. MJO phase 7 has the opposite effect on the background wave number 1 to MJO phase 4 (Figs. 9c,d). We also examined the responses of wave numbers 2 and 3 to high (low) occurrence frequency of MJO phases 4 and 7 (Fig. 10). The anomalous waves of wave number 2 in geopotential height anomalies during the high and low occurrence frequency years of MJO phase 4 do not overall superpose on the climatological stationary waves of wave number 2 in the vertical in the northern extratropics. There is an overall in-phase superposition between the anomalous wave number 3 waves and climatological stationary waves of wave number 3; however, the phases are opposite to those of wave number 1 during the high and low occurrence frequency years of MJO phase 4. In MJO phase 7, the anomalous waves of wave number 2 and 3 in geopotential height anomalies during the high and low occurrence frequency years do not overall superpose on climatological stationary waves of wave number 2 and 3 in the vertical in the northern extratropics. Therefore, only the wave number 1 responses to MJO in geopotential height anomalies are able to explain the stratospheric wave activity anomalies during the high and low occurrence frequency years of MJO phases 4 and 7. At this stage, a question is raised: Why do only the occurrence frequencies of MJO phase 4 and MJO phase 7 have a significant influence on wave activity in the northern extratropical stratosphere. Here, we further examine the effects of other MJO phases on wave activity in the extratropics. Figure 11 shows the geopotential height anomalies at 200 hPa during the high and low occurrence frequency years of MJO phases 1, 2, 3, 5, 6, and 8. It is apparent that the PNA like wave trains that propagate poleward to middle and high latitudes also develop during the high and low occurrence frequency years of these MJO phases. However, it can be seen from Fig. 12 that the geopotential height anomalies during the high and low occurrence frequency years of MJO phases 1, 2, 3, 5, 6, and 8 do not overall superpose on stationary waves of wave number 1 in the vertical in the extratropics. This illustrates that anomalous waves caused by these MJO phases do not efficiently interfere with the stationary waves of wave number 1; consequently, the occurrence frequency of MJO phases 1, 2, 3, 5, 6, and 8 have no significant influence on the wave activity of wave number 1 in the northern extratropical stratosphere. Figure 13 shows the wave number 2 geopotential height anomalies during the high and low occurrence frequencies of MJO phases 1, 2, 3, 5, 6, and 8. FIG. 10. As in Fig. 9, but for the wave numbers (a),(b),(e),(f) 2 and (c),(d),(g),(h) 3. The anomalous waves of wave number 2 during the high and low occurrence frequency years of MJO phases 2, 3, 5, and 6 do not overall superpose on the climatological stationary waves of wave number 2 in the northern extratropics; nonetheless, the influence of MJO phases 1 and 8 on wave number 2 cannot be neglected. This suggests that wave number 2 can be weakened (strengthened) in the high (low) occurrence frequency years of MJO phases 1 and 8. Figure 14 is the same as Fig. 13, but for wave number 3. The anomalous wave number 3 geopotential height anomalies during the high and low occurrence frequency years of MJO phases 1, 2, 6, and 8 do not overall superpose on the climatological stationary waves of wave number 3 in the northern extratropics. However, the geopotential height anomalies in the northern extratropics during the high (low) occurrence frequency years of MJO phase 3 are in the opposite (same) phase as the background wave number 3, weakening (enhancing) the strength of wave number 3. MJO phase 5 has the opposite effect on the background wave number 3 to MJO phase 3. Figures 13 and 14 suggest that the impacts of wave numbers 2 and 3 on interannual variations in stratospheric FIG. 11. As in Fig. 7, but for (top)–(bottom) MJO phases 1, 2, 3, 5, 6, and 8. wave activity can be triggered by MJO phases 1, 3, 5, or 8. However, the correlation coefficients between the E–P flux divergence anomalies and the occurrence frequency of MJO phases 1, 3, 5, and 8 are small and not significant (Fig. 2). In addition, previous studies have recognized that wave number 1 disturbances caused by the MJO are the dominant waves that propagate into the winter stratosphere and subsequently weaken the polar vortex (Garfinkel et al. 2012b, 2014). Thus, the wave number 1 responses to MJO phases can explain a large part of the variability in the stratospheric wave activity during the high and low occurrence frequency years of eight MJO phases. 5. Conclusions The effect of the MJO on wave activity in the extratropical stratosphere has been reported in several previous studies (Garfinkel et al. 2012b, 2014). However, these studies focused mainly on the relationship between these two processes over intraseasonal time scales. The present study has investigated the relationship between the occurrence frequency of the individual phases of the MJO and the interannual variability of stratospheric high frequency wave activity in Northern Hemisphere middle and high latitudes during winter over the period 1979–2013. We have found a significant positive correlation between the occurrence frequency of MJO phase 4 and E–P flux divergence anomalies; that is, higher (lower) occurrence frequency of MJO phase 4 corresponds to weaker (stronger) upward wave fluxes and increased (decreased) E–P flux divergence anomalies at middle and high latitudes in the middle and upper stratosphere. This implies depressed (enhanced) wave activity accompanied by a stronger (weaker) polar vortex in this region. During MJO phase 4, an anomalous PNA-like Rossby wave train is generated that travels north to the middle and high latitudes in the northern extratropical troposphere, and the geopotential height anomalies in FIG. 12. As in Fig. 9, but for (top)–(bottom) MJO phases 1, 2, 3, 5, 6, and 8. FIG. 13. As in Fig. 12, but for wavenumber 2. FIG. 14. As in Fig. 12, but for wavenumber 3. the high (low) occurrence frequency years of MJO phase 4 are of the opposite (same) phase as the background wave number 1 in the vertical in the northern extratropics. The pattern of convection anomaly during MJO phase 7 is approximately opposite to that during MJO phase 4, consequently, the responses of wave number 1 to high and low occurrence frequencies of MJO phase 7 are opposite to that of MJO phase 4. As MJO phase 7 has weaker convection anomalies, the effect of MJO phase 7 on the wave activity in the northern extratropical stratosphere is weaker than that of MJO phase 4. The anomalous waves in the geopotential height field caused by MJO phases 1, 2, 3, 5, 6, and 8 are not overally superposed on the climatological waves of wave number 1, and the wave interference between them is inefficient. Therefore, MJO phases 1, 2, 3, 5, 6, and 8 have no significant influence on the wave activity in the northern extratropical stratosphere. Acknowledgments. This work was supported by the National Science Foundation of China (41630421, 41575038, and 41575039). We thank the Australian Bureau of Meteorology for providing the MJO index, and NOAA for providing the OLR data and OOMI. We would also thank the NCEP–NCAR and ECMWF for providing the reanalysis data. We thank the three anonymous reviewers for their helpful comments, which significantly improved the quality of the paper. REFERENCES Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle At- mosphere Dynamics. Academic Press, 489 pp. Butchart, N., and Coauthors, 2006: Simulations of anthropogenic change in the strength of the Brewer–Dobson circulation. Climate Dyn., 27, 727–741, https://doi.org/10.1007/s00382-006-0162-4. Cagnazzo, C., and E. Manzini, 2009: Impact of the stratosphere on the winter tropospheric teleconnections between ENSO and the North Atlantic and European region. J. Climate, 22, 1223– 1238, https://doi.org/10.1175/2008JCLI2549.1. ——, and Coauthors, 2009: Northern winter stratospheric tem- perature and ozone responses to ENSO inferred from an en- semble of chemistry climate models. Atmos. Chem. Phys., 9, 8935–8948, https://doi.org/10.5194/acp-9-8935-2009. Calvo Fernández, N., R. R. García, R. García Herrera, D. Gallego Puyol, L. Gimeno Presa, E. Hernández Martín, and P. Ribera Rodríguez, 2004: Analysis of the ENSO signal in tropospheric and stratospheric temperatures observed by MSU, 1979–2000. J. Climate, 17, 3934–3946, https://doi.org/10.1175/1520- 0442(2004)017,3934:AOTESI.2.0.CO;2. ——, M. A. Giorgetta, R. G. Herrera, and E. Manzini, 2009: Nonlinearity of the combined warm ENSO and QBO effects on the Northern Hemisphere polar vortex in MAECHAM5 simulations. J. Geophys. Res., 114, D13109, https://doi.org/ 10.1029/2008JD011445. Camp, C. D., and K.-K. Tung, 2007: Stratospheric polar warming by ENSO in winter: A statistical study. Geophys. Res. Lett., 34, L04809, https://doi.org/10.1029/2006GL028521. Cassou, C., 2008: Intraseasonal interaction between the Madden– Julian oscillation and the North Atlantic Oscillation. Nature, 455, 523–527, https://doi.org/10.1038/nature07286. Chen, X., J. Ling, and C. Li, 2016: Evolution of the Madden–Julian oscillation in two types of El Niño. J. Climate, 29, 1919–1934, https://doi.org/10.1175/JCLI-D-15-0486.1. Cohen, J., and J. Jones, 2011: A new index for more accurate winter predictions. Geophys. Res. Lett., 38, L21701, https://doi.org/ 10.1029/2011GL049626. Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Con- figuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828. Deng, L., T. Li, J. Liu, and M. Peng, 2016: Factors controlling the interannual variations of MJO intensity. J. Meteor. Res., 30, 328–340, https://doi.org/10.1007/s13351-016-5113-3. Edmon, H. J., Jr., B. J. Hoskins, and M. E. McIntyre, 1980: Eliassen– Palm cross sections for the troposphere. J. Atmos. Sci., 37, 2600– 2616, https://doi.org/10.1175/1520-0469(1980)037,2600: EPCSFT.2.0.CO;2. Garcia, R. R., and W. J. Randel, 2008: Acceleration of the Brewer– Dobson circulation due to increases in greenhouse gases. J. Atmos. Sci., 65, 2731–2739, https://doi.org/10.1175/2008JAS2712.1. ——, D. R. Marsh, D. E. Kinnison, B. A. Boville, and F. Sassi, 2007: Simulation of secular trends in the middle atmosphere, 1950– 2003. J. Geophys. Res., 112, D09301, https://doi.org/10.1029/ 2006JD007485. Garfinkel, C. I., and D. L. Hartmann, 2008: Different ENSO tele- connections and their effects on the stratospheric polar vortex. J. Geophys. Res., 113, D18114, https://doi.org/10.1029/ 2008JD009920. ——, T. A. Shaw, D. L. Hartmann, and D. W. Waugh, 2012a: Does the Holton–Tan mechanism explain how the quasi-biennial oscillation modulates the Arctic polar vortex? J. Atmos. Sci., 69, 1713–1733, https://doi.org/10.1175/JAS-D-11-0209.1. ——, S. B. Feldstein, D. W. Waugh, C. Yoo, and S. Lee, 2012b: Observed connection between stratospheric sudden warmings and the Madden–Julian oscillation. Geophys. Res. Lett., 39, L18807, https://doi.org/10.1029/2012GL053144. ——, J. J. Benedict, and E. D. Maloney, 2014: Impact of the MJO on the boreal winter extratropical circulation. Geophys. Res. Lett., 41, 6055–6062, https://doi.org/10.1002/2014GL061094. ——, M. M. Hurwitz, and L. D. Oman, 2015: Effect of recent sea surface temperature trends on the Arctic stratospheric vortex. J. Geophys. Res. Atmos., 120, 5404–5416, https://doi.org/10.1002/ 2015JD023284. Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447–462, https:// doi.org/10.1002/qj.49710644905. Holland, M. M., D. A. Bailey, B. P. Briegleb, B. Light, and E. Hunke, 2012: Improved sea ice shortwave radiation physics in CCSM4: The impact of melt ponds and aerosols on Arctic sea ice. J. Climate, 25, 1413–1430, https://doi.org/10.1175/JCLI-D-11-00078.1. Holton, J. R., and H.-C. Tan, 1980: The influence of the equa- torial quasi-biennial oscillation on the global circulation at 50 mb. J. Atmos. Sci., 37, 2200–2208, https://doi.org/10.1175/ 1520-0469(1980)037,2200:TIOTEQ.2.0.CO;2. ——, and ——, 1982: The quasi-biennial oscillation in the Northern Hemisphere lower stratosphere. J. Meteor. Soc. Japan, 60, 140–148, https://doi.org/10.2151/jmsj1965.60.1_140. Hoskins, B. J., and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forc- ing. J. Atmos. Sci., 38, 1179–1196, https://doi.org/10.1175/ 1520-0469(1981)038,1179:TSLROA.2.0.CO;2. ——, and T. Ambrizzi, 1993: Rossby wave propagation on a realistic longitudinally varying flow. J. Atmos. Sci., 50, 1661–1671, https:// doi.org/10.1175/1520-0469(1993)050,1661:RWPOAR.2.0.CO;2. Hu, Y., and K. K. Tung, 2003: Possible ozone-induced long-term changes in planetary wave activity in late winter. J. Climate, 16, 3027–3038, https://doi.org/10.1175/1520-0442(2003)016,3027: POLCIP.2.0.CO;2. Hurrell, J. W., and Coauthors, 2013: The Community Earth Sys- tem Model: A framework for collaborative research. Bull. Amer. Meteor. Soc., 94, 1339–1360, https://doi.org/10.1175/ BAMS-D-12-00121.1. Hurwitz, M. M., P. A. Newman, and C. I. Garfinkel, 2012: On the influence of North Pacific sea surface temperature on the Arctic winter climate. J. Geophys. Res., 117, D19110, https:// doi.org/10.1029/2012JD017819. Inness, P. M., and J. M. Slingo, 2003: Simulation of the Madden– Julian oscillation in a coupled general circulation model. Part I: Comparison with observations and an atmosphere- only GCM. J. Climate, 16, 345–364, https://doi.org/10.1175/ 1520-0442(2003)016,0345:SOTMJO.2.0.CO;2. IPCC, 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp. Johnson, N. C., and S. B. Feldstein, 2010: The continuum of North Pacific sea level pressure patterns: Intraseasonal, interannual, and interdecadal variability. J. Climate, 23, 851–867, https:// doi.org/10.1175/2009JCLI3099.1. Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Re- analysis Project. Bull. Amer. Meteor. Soc., 77, 437–471, https:// doi.org/10.1175/1520-0477(1996)077,0437:TNYRP.2.0.CO;2. Kang, W., and E. Tziperman, 2017: More frequent sudden strato- spheric warming events due to enhanced MJO forcing ex- pected in a warmer climate. J. Climate, 30, 8727–8743, https:// doi.org/10.1175/JCLI-D-17-0044.1. Karpechko, A. Y., and E. Manzini, 2012: Stratospheric influence on tropospheric climate change in the Northern Hemi- sphere. J. Geophys. Res., 117, D05133, https://doi.org/10.1029/ 2011JD017036. Kim, B.-M., S.-W. Son, S.-K. Min, J.-H. Jeong, S.-J. Kim, X. Zhang, T. Shim, and J.-H. Yoon, 2014: Weakening of the stratospheric polar vortex by Arctic sea-ice loss. Nat. Com- mun., 5, 4646, https://doi.org/10.1038/ncomms5646. Kuroda, Y., and K. Kodera, 1999: Role of planetary waves in the stratosphere–troposphere coupled variability in the Northern Hemisphere winter. Geophys. Res. Lett., 26, 2375–2378, https://doi.org/10.1029/1999GL900507. Kushner, P. J., and L. M. Polvani, 2004: Stratosphere– troposphere coupling in a relatively simple AGCM: The role of eddies. J. Climate, 17, 629–639, https://doi.org/10.1175/ 1520-0442(2004)017,0629:SCIARS.2.0.CO;2. Lean, J., G. Rottman, J. Harder, and G. Kopp, 2005: SORCE contributions to new understanding of global change and solar variability. Sol. Phys., 230, 27–53, https://doi.org/10.1007/ s11207-005-1527-2. L’Heureux, M. L., and R. W. Higgins, 2008: Boreal winter links be- tween the Madden–Julian oscillation and the Arctic Oscillation. J. Climate, 21, 3040–3050, https://doi.org/10.1175/2007JCLI1955.1. Li, K.-F., B. Tian, K. K. Tung, L. Kuai, J. R. Worden, Y. L. Yung, and B. L. Slawski, 2013: A link between tropical intraseasonal variability and Arctic stratospheric ozone. J. Geophys. Res. Atmos., 118, 4280–4289, https://doi.org/10.1002/jgrd.50391. Li, Y., and J. Li, 2012: Propagation of planetary waves in the hori- zontal non-uniform basic flow (in Chinese). Chin. J. Geophys., 55, 361–371. ——, ——, F. F. Jin, and S. Zhao, 2015: Interhemispheric propa- gation of stationary Rossby waves in a horizontally non- uniform background flow. J. Atmos. Sci., 72, 3233–3256, https://doi.org/10.1175/JAS-D-14-0239.1. Lin, H., G. Brunet, and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden– Julian oscillation. J. Climate, 22, 364–380, https://doi.org/ 10.1175/2008JCLI2515.1. ——, ——, and B. Yu, 2015: Interannual variability of the Madden– Julian oscillation and its impact on the North Atlantic Oscil- lation in the boreal winter. Geophys. Res. Lett., 42, 5571–5576, https://doi.org/10.1002/2015GL064547. Liu, C., B. Tian, K.-F. Li, G. L. Manney, N. J. Livesey, Y. L. Yung, and D. E. Waliser, 2014: Northern Hemisphere mid-winter vortex-displacement and vortex-split stratospheric sudden warmings: Influence of the Madden–Julian oscillation and quasi-biennial oscillation. J. Geophys. Res. Atmos., 119, 12 599–12 620, https://doi.org/10.1002/2014JD021876. ——, Y. Liu, and Y.-L. Zhang, 2015: Simulation of the Madden– Julian oscillation in wintertime stratospheric ozone over the Tibetan Plateau and East Asia: Results from the Specified Dynamics version of the Whole Atmosphere Community Climate Model. Atmos. Ocean. Sci. Lett., 8, 264–270, https:// doi.org/10.3878/AOSL20150020. Lu, H., T. J. Bracegirdle, T. Phillips, A. Bushell, and L. Gray, 2014: Mechanisms for the Holton–Tan relationship and its decadal variation. J. Geophys. Res. Atmos., 119, 2811–2830, https://doi.org/ 10.1002/2013JD021352. Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702–708, https://doi.org/10.1175/1520-0469(1971)028,0702: DOADOI.2.0.CO;2. ——, and ——, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 1109–1123, https://doi.org/10.1175/1520-0469(1972)029,1109: DOGSCC.2.0.CO;2. ——, and ——, 1994: Observations of the 40–50-day tropical oscil- lation—A review. Mon. Wea. Rev., 122, 814–837, https://doi.org/ 10.1175/1520-0493(1994)122,0814:OOTDTO.2.0.CO;2. Manzini, E., M. A. Giorgetta, M. Esch, L. Kornblueh, and E. Roeckner, 2006: The influence of sea surface temperatures on the northern winter stratosphere: Ensemble simulations with the MAECHAM5 model. J. Climate, 19, 3863–3881, https://doi.org/10.1175/JCLI3826.1. Marsh, D. R., M. J. Mills, D. E. Kinnison, J.-F. Lamarque, N. Calvo, and L. M. Polvani, 2013: Climate change from 1850 to 2005 simulated in CESM1(WACCM). J. Climate, 26, 7372– 7391, https://doi.org/10.1175/JCLI-D-12-00558.1. Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area. J. Meteor. Soc. Japan, 44, 25–43, https://doi.org/10.2151/ jmsj1965.44.1_25. Matthews, A. J., B. J. Hoskins, and M. Masutani, 2004: The global response to tropical heating in the Madden–Julian oscillation during the northern winter. Quart. J. Roy. Meteor. Soc., 130, 1991–2011, https://doi.org/10.1256/qj.02.123. Mori, M., and M. Watanabe, 2008: The growth and triggering mechanism of the PNA: A MJO–PNA coherence. J. Meteor. Soc. Japan, 86, 213–236, https://doi.org/10.2151/jmsj.86.213. Neale, R. B., J. Richter, S. Park, P. H. Lauritzen, S. J. Vavrus, P. J. Rasch, and M. H. Zhang, 2013: The mean climate of the Community Atmosphere Model (CAM4) in forced SST and fully coupled experiments. J. Climate, 26, 5150–5168, https:// doi.org/10.1175/JCLI-D-12-00236.1. Newman, M., and P. D. Sardeshmukh, 2008: Tropical and strato- spheric influences on extratropical short-term climate vari- ability. J. Climate, 21, 4326–4347, https://doi.org/10.1175/ 2008JCLI2118.1. Newman, P. A., and E. R. Nash, 2000: Quantifying the wave driving of the stratosphere. J. Geophys. Res., 105, 12 485–12 497, https://doi.org/10.1029/1999JD901191. Perlwitz, J., and H.-F. Graf, 2001: Troposphere–stratosphere dy- namic coupling under strong and weak polar vortex condi- tions. Geophys. Res. Lett., 28, 271–274, https://doi.org/10.1029/ 2000GL012405. ——, and N. Harnik, 2004: Downward coupling between the stratosphere and troposphere: The relative roles of wave and zonal mean processes. J. Climate, 17, 4902–4909, https://doi.org/ 10.1175/JCLI-3247.1. Polvani, L. M., and D. W. Waugh, 2004: Upward wave activity flux as a precursor to extreme stratospheric events and subsequent anom- alous surface weather regimes. J. Climate, 17, 3548–3554, https:// doi.org/10.1175/1520-0442(2004)017,3548:UWAFAA.2.0.CO;2. Randel, W. J., F. Wu, and R. Stolarski, 2002: Changes in column ozone correlated with the stratospheric EP flux. J. Meteor. Soc. Japan, 80, 849–862, https://doi.org/10.2151/jmsj.80.849. Ren, R.-C., M. Cai, C. Xiang, and G. Wu, 2012: Observational evidence of the delayed response of stratospheric polar vortex variability to ENSO SST anomalies. Climate Dyn., 38, 1345– 1358, https://doi.org/10.1007/s00382-011-1137-7. Schwartz, C., and C. I. Garfinkel, 2017: Relative roles of the MJO and stratospheric variability in North Atlantic and European winter climate. J. Geophys. Res. Atmos., 122, 4184–4201, https://doi.org/10.1002/2016JD025829. Seo, K.-H., and S.-W. Son, 2012: The global atmospheric circula- tion response to tropical diabatic heating associated with the Madden–Julian oscillation during northern winter. J. Atmos. Sci., 69, 79–96, https://doi.org/10.1175/2011JAS3686.1. Subramanian, A. C., M. Jochum, A. J. Miller, R. Murtugudde, R. Neale, R. B. Neale, and D. E. Waliser, 2011: The Madden– Julian oscillation in CCSM4. J. Climate, 24, 6261–6282, https:// doi.org/10.1175/JCLI-D-11-00031.1. Sun, C., J. Li, and S. Zhao, 2015: Remote influence of At- lantic multidecadal variability on Siberian warm season precipitation. Sci. Rep., 5, 16853, https://doi.org/10.1038/ srep16853. ——, ——, R. Ding, and Z. Jin, 2017: Cold season Africa–Asia multidecadal teleconnection pattern and its relation to the Atlantic multidecadal variability. Climate Dyn., 48, 3903– 3918, https://doi.org/10.1007/s00382-016-3309-y. Thompson, D. W. J., and J. M. Wallace, 2001: Regional climate impacts of the Northern Hemisphere annular mode. Science, 293, 85–89, https://doi.org/10.1126/science.1058958. Wheeler, M. C., and H. H. Hendon, 2004: An all-season real- time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932, https://doi.org/10.1175/1520-0493(2004)132,1917: AARMMI.2.0.CO;2. Wu, Z., X. Li, Y. Li, and Y. Li, 2016: Potential influence of Arctic sea ice to the interannual variations of East Asian spring precipitation. J. Climate, 29, 2797–2813, https://doi.org/10.1175/ JCLI-D-15-0128.1. Xie, F., J. Li, W. Tian, J. Feng, and Y. Huo, 2012: Signals of El Niño Modoki in the tropical tropopause layer and stratosphere. Atmos. Chem. Phys., 12, 5259–5273, https://doi.org/10.5194/ acp-12-5259-2012. ——, and Coauthors, 2016: A connection from Arctic stratospheric ozone to El Niño–Southern Oscillation. Environ. Res. Lett., 11, 124026, https://doi.org/10.1088/1748-9326/11/12/124026. Xu, H., J. Li, J. Feng, and J. Mao, 2013: The asymmetric relation- ship between the winter NAO and the precipitation in southwest China. Acta Meteor. Sin., 70, 1276–1291. Yang, C., T. Li, A. K. Smith, and X. Dou, 2017: The response of the Southern Hemisphere middle atmosphere to the Madden–Julian oscillation during austral winter using the Specified-Dynamics Whole Atmosphere Community Cli- mate Model. J. Climate, 30, 8317–8333, https://doi.org/10.1175/ JCLI-D-17-0063.1. Yoo, C., S. Feldstein, and S. Lee, 2011: The impact of the Madden– Julian oscillation trend on the Arctic amplification of surface air temperature during the 1979–2008 boreal winter. Geophys. Res. Lett., 38, L24804, https://doi.org/10.1029/2011GL049881. ——, S. Lee, and S. B. Feldstein, 2012: Mechanisms of Arctic surface air temperature change in response to the Madden– Julian oscillation. J. Climate, 25, 5777–5790, https://doi.org/ 10.1175/JCLI-D-11-00566.1. Zhang, C., M. Dong, S. Gualdi, H. H. Hendon, E. D. Maloney, A. Marshall, K. R. Sperber, and W. Wang, 2006: Simulations of the Madden–Julian oscillation in four pairs of coupled and uncoupled global models. Climate Dyn., 27, 573–592, https:// doi.org/10.1007/s00382-006-0148-2. Zhang, J., W. Tian, F. Xie, Y. Li, F. Wang, J. Huang, and H. Tian, 2015a: Influence of the El Niño Southern Oscillation on the total ozone column and clear-sky ultraviolet radiation over China. Atmos. Environ., 120, 205–216, https://doi.org/10.1016/ j.atmosenv.2015.08.080. ——, ——, Z. Wang, F. Xie, and F. Wang, 2015b: The influence of ENSO on northern midlatitude ozone during the winter to spring transition. J. Climate, 28, 4774–4793, https://doi.org/ 10.1175/JCLI-D-14-00615.1. ——, ——, M. P. Chipperfield, F. Xie, and J. Huang, 2016: Per- sistent shift of the Arctic polar vortex towards the Eurasian continent in recent decades. Nat. Climate Change, 6, 1094– 1099, https://doi.org/10.1038/nclimate3136. Zhao, S., J. Li, and Y. Li, 2015: Dynamics of an interhemispheric teleconnection across the critical latitude through a southerly duct during boreal winter. J. Climate, 28, 7437–7456, https:// doi.org/10.1175/JCLI-D-14-00425.1. Zheng, F., J. Li, Y. Li, S. Zhao, and D. Deng, 2016: Influence of the summer NAO on the spring-NAO-based predictability of the East Asian summer monsoon. J. Appl. Meteor. Climatol., 55, 1459–1476, https://doi.org/10.1175/JAMC-D-15-0199.1. Zhou, S., and A. J. Miller, 2005: The interaction of the Madden– Julian oscillation and the Arctic Oscillation. J. Climate, 18, 143–159, https://doi.org/10.1175/JCLI3251.1.
  16. Are Multiple Tropical Cyclone Events Similar among Basins? Authors: Benjamin A. Schenkel Published: 22nd May, 2017 Abstract: The present study intercompares multiple tropical cyclone event (MTCE) characteristics among each global tropical cyclone (TC) basin using best-track data. Specific focus is placed on examining the number of MTCEs and TCs during MTCEs, the zonal distance between TCs during MTCEs, and the spatiotemporal separation between genesis events during MTCEs. The results suggest that the ratio of MTCEs relative to single TCs is substantially higher in the eastern North Pacific (ENP), western North Pacific (WNP), and south Indian Ocean (SI) basins compared to the North Atlantic (NA) and South Pacific (SP). The prolific nature of ENP, WNP, and SI MTCE activity results in approximately half of TCs occurring during MTCEs. During new TC genesis, the majority of preexisting TCs are generally located westward at a consistent zonal distance from new TC genesis for MTCEs within each basin with median values between −1620 and −1961 km. TC-induced Rossby wave dispersion may set this zonal length scale as implied by its moderate-to-strong correlations (R = 0.38–0.85; p < 0.05) with the shallow-water zonal wavelength of TC-induced stationary Rossby waves. A substantial majority of TC genesis events occur progressively eastward during ENP, WNP, and SP MTCEs, whereas NA and SI MTCEs exhibit no such tendency. Last, the temporal separation between the genesis of preexisting and new TCs is generally similar among basins with median values between 3 and 4 days. Together, these results are indicative of unusual similarity in MTCE characteristics among basins despite differences in environmental and TC characteristics in each basin. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-17-0088.1
  17. Kelvin Waves and Tropical Cyclogenesis: A Global Survey Authors: Carl J. Schreck III Published: 15th June, 2015 Abstract: Convectively coupled atmospheric Kelvin waves are among the most prominent sources of synoptic-scale rainfall variability in the tropics, but large uncertainties surround their role in tropical cyclogenesis. This study identifies the modulation of tropical cyclones relative to the passage of a Kelvin wave’s peak rainfall (i.e., its crest) in each basin. Tropical cyclogenesis is generally inhibited for 3 days before the crest and enhanced for 3 days afterward. Composites of storms forming in the most favorable lags illustrate the dynamical impacts of the waves. In most basins, the tropical cyclone actually forms during the convectively suppressed phase of the wave. The 850-hPa equatorial westerly anomalies provide the cyclonic vorticity for the nascent storm, and 200-hPa easterly anomalies enhance the outflow. The wind anomalies persist at both levels longer than the Kelvin wave’s period and are often related to the Madden–Julian oscillation (MJO). The onset of these wind anomalies occurs with the Kelvin wave passage, while the MJO apparently establishes their duration. Many of the composites also show evidence of an easterly wave from which the tropical cyclone develops. The composite easterly wave amplifies or even initiates within the Kelvin wave crest. These results show the importance of Kelvin waves interacting with the MJO and easterly waves during tropical cyclogenesis. Given that Kelvin waves often circumnavigate the globe, these results show promise for long-range forecasting of tropical cyclogenesis in all basins. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-15-0111.1
  18. Examining Tropical Cyclone–Kelvin Wave Interactions Using Adjoint Diagnostics Authors: Carolyn A. Reynolds, James D. Doyle, and Xiaodong Hong Published: 16th August, 2016 Abstract: The initial-state sensitivity and interactions between a tropical cyclone and atmospheric equatorial Kelvin waves associated with the Madden–Julian oscillation (MJO) during the DYNAMO field campaign are explored using adjoint-based tools from the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). The development of Tropical Cyclone 5 (TC05) coincided with the passage of an equatorial Kelvin wave (KW) and westerly wind burst associated with an MJO that developed in the Indian Ocean in late November 2011. COAMPS 18-h adjoint sensitivities of low-level kinetic energy to changes in initial state winds, temperature, and water vapor are analyzed for both TC05 and the KW to document when the evolution of each system is sensitive to the other. Time series of sensitivity patterns confirm that TC05 and the KW low-level westerlies are sensitive to each other when the KW is to the southwest and south of TC05. While TC05 is not sensitive to the KW after this, the KW low-level westerlies remain sensitive to TC05 until it enters the far eastern Indian Ocean. Vertical profiles of both TC05 and KW sensitivity indicate lower-tropospheric maxima in temperature, wind, and moisture, with KW sensitivity typically 20% smaller than TC05 sensitivity. The magnitude of the sensitivity for both systems is greatest just prior to, and during, their closest proximity. A case study examination reveals that adjoint-based optimal perturbations grow and expand quickly through a dynamic response to decreased static stability. The evolution of moist-only and dry-only initial perturbations illustrates that the moist component is primarily responsible for the initial rapid growth, but that subsequent growth rates are similar. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-16-0174.1
  19. Subseasonal Forecasts of Convectively Coupled Equatorial Waves and the MJO: Activity and Predictive Skill Authors: Matthew A. Janiga, Carl J. Schreck III, James A. Ridout, Maria Flatau, Neil P. Barton, E. Joseph Metzger and Carolyn A. Reynolds Published: 30th March, 2018 (published online; 16th July, 2018) Abstract: In this study, the contribution of low-frequency (>100 days), Madden–Julian oscillation (MJO), and convectively coupled equatorial wave (CCEW) variability to the skill in predicting convection and winds in the tropics at weeks 1–3 is examined. We use subseasonal forecasts from the Navy Earth System Model (NESM); NCEP Climate Forecast System, version 2 (CFSv2); and ECMWF initialized in boreal summer 1999–2015. A technique for performing wavenumber–frequency filtering on subseasonal forecasts is introduced and applied to these datasets. This approach is better able to isolate regional variations in MJO forecast skill than traditional global MJO indices. Biases in the mean state and in the activity of the MJO and CCEWs are smallest in the ECMWF model. The NESM overestimates cloud cover as well as MJO, equatorial Rossby, and mixed Rossby–gravity/tropical depression activity over the west Pacific. The CFSv2 underestimates convectively coupled Kelvin wave activity. The predictive skill of the models at weeks 1–3 is examined by decomposing the forecasts into wavenumber–frequency signals to determine the modes of variability that contribute to forecast skill. All three models have a similar ability to simulate low-frequency variability but large differences in MJO skill are observed. The skill of the NESM and ECMWF model in simulating MJO-related OLR signals at week 2 is greatest over two regions of high MJO activity, the equatorial Indian Ocean and Maritime Continent, and the east Pacific. The MJO in the CFSv2 is too slow and too weak, which results in lower MJO skill in these regions. Link to full paper: https://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-17-0261.1
  20. Intraseasonal Tropical Cyclogenesis Prediction in a Global Coupled Model System Authors: Xianan Jiang, Baoqiang Xiang, Ming Zhao, Tim Li, Shian-Jiann Lin, Zhuo Wang and Jan-Huey Chen Published: 10th April, 2018 (published online; 10th July, 2018) Abstract: Motivated by increasing demand in the community for intraseasonal predictions of weather extremes, predictive skill of tropical cyclogenesis is investigated in this study based on a global coupled model system. Limited intraseasonal cyclogenesis prediction skill with a high false alarm rate is found when averaged over about 600 tropical cyclones (TCs) over global oceans from 2003 to 2013, particularly over the North Atlantic (NA). Relatively skillful genesis predictions with more than 1-week lead time are only evident for about 10% of the total TCs. Further analyses suggest that TCs with relatively higher genesis skill are closely associated with the Madden–Julian oscillation (MJO) and tropical synoptic waves, with their geneses strongly phase-locked to the convectively active region of the MJO and low-level cyclonic vorticity associated with synoptic-scale waves. Moreover, higher cyclogenesis prediction skill is found for TCs that formed during the enhanced periods of strong MJO episodes than those during weak or suppressed MJO periods. All these results confirm the critical role of the MJO and tropical synoptic waves for intraseasonal prediction of TC activity. Tropical cyclogenesis prediction skill in this coupled model is found to be closely associated with model predictability of several large-scale dynamical and thermodynamical fields. Particularly over the NA, higher predictability of low-level relative vorticity, midlevel humidity, and vertical zonal wind shear is evident along a tropical belt from the West Africa coast to the Caribbean Sea, in accord with more predictable cyclogenesis over this region. Over the extratropical NA, large-scale variables exhibit less predictability due to influences of extratropical systems, leading to poor cyclogenesis predictive skill. Link to full paper: http://climvar.org/jiang/pub/jiang_jcl2018_tc_predictability.pdf
  21. Climate science in the tropics: waves, vortices and PDEs Authors: Boualem Khouider, Andrew J Majda and Samuel N Stechmann Published: 16th November, 2012 Abstract: Clouds in the tropics can organize the circulation on planetary scales and profoundly impact long range seasonal forecasting and climate on the entire globe, yet contemporary operational computer models are often deficient in representing these phenomena. On the other hand, contemporary observations reveal remarkably complex coherent waves and vortices in the tropics interacting across a bewildering range of scales from kilometers to ten thousand kilometers. This paper reviews the interdisciplinary contributions over the last decade through the modus operandi of applied mathematics to these important scientific problems. Novel physical phenomena, new multiscale equations, novel PDEs, and numerical algorithms are presented here with the goal of attracting mathematicians and physicists to this exciting research area. Link to full paper: https://www.math.nyu.edu/faculty/majda/pdfFiles/Nonlinearity_MajdaKhouiderStechmann_3.17.12.pdf
  22. Kelvin Waves and Tropical Cyclogenesis in a Lagrangian Framework - Presentation A presentation at the AMS 32nd Conference on “Hurricanes and Tropical Meteorology” held at the Condado Plaza Hilton in Puerto Rico between 17th and 22nd April, 2016. Presenters: Carl J. Schreck III  Presentation Date: 18th April, 2016 Presentation Summary: Recent work has shown that tropical cyclogenesis is favored 0�3 days after Kelvin wave passage. Other studies have shown the utility of a Lagrangian framework for identifying the recirculation of moisture within easterly waves. This recirculation ultimately leads to tropical cyclogenesis within the wave's �pouch.� This study examines the role of the equatorial westerlies from Kelvin waves in helping to close the Lagrangian circulation. The vertical tilt of Kelvin waves results in these westerlies reaching mid-levels about 3 days after the convection passing, which may explain the delay between Kelvin wave passage and cyclogenesis. Given that Kelvin waves frequently circumnavigate the globe, these results may provide a framework for long range tropical cyclogenesis forecasting. Link to conference video presentation (14 minutes): https://ams.confex.com/ams/32Hurr/videogateway.cgi/id/33474?recordingid=33474 Link to Handout - charts only: https://ams.confex.com/ams/32Hurr/webprogram/Paper293105.html (pdf file via conference presentation summary) Link to full conference agenda: https://ams.confex.com/ams/32Hurr/webprogram/32HURRICANES.html
  23. Impact of the Boreal Summer Quasi-biweekly Oscillation on Eastern North Pacific Tropical Cyclone Activity - Presentation A presentation at the AMS 33rd Conference on “Hurricanes and Tropical Meteorology” held at Ponte Vedra, Florida, USA between 16th and 20th April, 2018 Presenters: Haikun Zhao Presentation Date: 19th April, 2018  Presentation Summary: Several studies have focused on the impact of the Madden-Julian Oscillation (MJO, with a period between 30-60 days) on boreal summer tropical cyclone (TC) activity over the Eastern North Pacific (ENP) basin. The quasi-biweekly oscillation (QBWO), with a period of about 20 days, is another dominant mode of intra-seasonal variability during the boreal summer over the ENP basin. There have been fewer studies focused on the influence of the QBWO on tropical cyclogenesis over the ENP basin. The exploratory analyses performed in this study suggest that the QBWO has a strong impact on boreal summer ENP TC activity, with enhanced TC activity during the convectively active phase. The significant increase (decrease) of tropical cyclogenesis events during the convectively active (inactive) QBWO phase is found to be closely associated with the strengthening (weakening) of the low-level cyclonic circulation and increasing (decreasing) mid-level relative humidity (vertical wind shear) over the ENP. Mid-level relative humidity and low-level vorticity are found to be the two most important players in modulating TC genesis location and frequency, based upon the analyses of the anomalous genesis potential index (GPI) pattern and its magnitude associated with the QBWO. Associated with changes in TC location and large-scale steering flows, distinct difference in TC tracks during different QBWO phases can be readily found and thus cause substantial differences in basin-wide TC intensity. This study enhances our understanding of the modulation of intra-seasonal oscillations on boreal summer ENP TC activity and has the potential to aid in the sub-seasonal prediction of ENP TC activity.  Link to conference video presentation (15 minutes): https://ams.confex.com/ams/33HURRICANE/videogateway.cgi/id/46985?recordingid=46985&amp;uniqueid=Paper340276&amp;entry_password=310623 Link to full conference agenda: https://ams.confex.com/ams/33HURRICANE/webprogram/33HURRICANE.html
  24. Planetary Scale Intraseasonal Disturbances - Presentation A presentation at the AMS 33rd Conference on “Hurricanes and Tropical Meteorology” held at Ponte Vedra, Florida, USA between 16th and 20th April, 2018 Presenters: Zeljka Fuchs, Socorro, NM and D. J. Raymond Presentation Date: 19th April, 2018  Presentation Summary: There are two planetary disturbances that by definition prefer long wavelengths. One moves eastward and is associated with the Madden-Julian oscillation, while another moves westward and is called the Rossby wave. Using the simple linear analytical model on an equatorial beta plane we model two unstable modes, eastward at meridional number n=-1 and westward propagating mode at meridional number n=1. Both of those modes are moisture modes, but the instability mechanism is not necessarily associated with the moisture mode instability, i.e. the negative gross-moist instability and cloud-radiation interactions. Instead the primary cause for the instability is mean easterlies. This makes sense when modeling the planetary disturbances as mean easterlies are present in the real atmosphere on a planetary scale due to the Hadley cell (GMS and CRI do not scale as planetary mechanisms). We speculate that our modeled eastward and westward propagating WISHE-moisture modes incorporate the basics of physics for the MJO and Rossby waves. Other effects as well as the nonlinearity play an important role, but the essence of the MJO and Rossby waves, according to our model, only requires mean easterlies and moisture mode physics.  Link to conference video presentation (15 minutes): https://ams.confex.com/ams/33HURRICANE/videogateway.cgi/id/46983?recordingid=46983&amp;uniqueid=Paper340106&amp;entry_password=166057 Link to full conference agenda: https://ams.confex.com/ams/33HURRICANE/webprogram/33HURRICANE.html
  25. Circumglobal Propagation of Successive MJO Events in MERRA-2 - Presentation A presentation at the AMS 33rd Conference on “Hurricanes and Tropical Meteorology” held at Ponte Vedra, Florida, USA between 16th and 20th April, 2018 Presenters: Scott W. Powell Presentation Date: 19th April, 2018  Presentation Summary: The propagation speeds of strong circumnavigating, successive MJO events are examined in MERRA-2 reanalysis. The MJO cases are tracked by following large-scale vertical motion anomalies with zonal wavenumber of 1–2. Statistically significant signals of parameterized latent heating and adiabatic cooling are co-located with the vertical motion anomalies. They move through the equatorial Western Hemisphere at roughly 20–30 m s-1 but much slower—about 5 m s-1—over the tropical warm pool. The theoretically expected phase speed of the convectively coupled circumnavigating wave is also computed following theory of Neelin and Held (1997) and Emanuel et al. (1994): Reduction of effective static stability felt by the wave—caused by the climatological offset between column integrated diabatic heating and adiabatic cooling in the low-wavenumber MJO signal—makes the phase speed less than that of a corresponding dry, freely propagating wave. The offset computed using MERRA-2 output is robust from year to year and at all longitudes in the Tropics. The above method predicts that a first baroclinic mode should propagate 20–25 m s-1 over much of the Western Hemisphere, 20–35 m s-1 over the eastern Atlantic and Africa, and 5–20 m s-1 over the tropical warm pool, similar—for the Western Hemisphere—to the rates actually seen in reanalysis. The result lends support to the idea that the circumnavigating MJO is a first baroclinic convectively coupled Kelvin wave. However, in places where widespread deep convection is prevalent and the offset between diabatic heating and adiabatic cooling is large (i.e. the warm pool), the theory overestimates propagation speed. Rather, moisture wave theories are more effective at capturing the slow propagation speed of the MJO over the warm pool. Therefore, two distinct dynamic regimes—one in which gravity waves dominate and another in which moisture wave dynamics may be more applicable—govern MJO propagation depending on where its signal is located. This study motivates the need for a holistic MJO theory that contains both elements of its propagation and the transitions of the MJO from a Kelvin wave to a moisture wave, and vice versa, as it sometimes propagates around the world.  Link to conference video presentation (14 minutes): https://ams.confex.com/ams/33HURRICANE/videogateway.cgi/id/46979?recordingid=46979&amp;uniqueid=Paper340198&amp;entry_password=256413 Link to full conference agenda: https://ams.confex.com/ams/33HURRICANE/webprogram/33HURRICANE.html
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