Tropical Intraseasonal Variability Research Articles

Distinct propagating and standing modes of tropical intraseasonal variability as represented by the two principal oscillation patterns

Although the tropical intraseaonal variability (TISV), as the most important predictability sources for subseasonal-to-seasonal (S2S) prediction, is dominated by Madden-Julian oscillation (MJO), its significant fraction does not always share the canonical MJO features, especially when the convective activity arrives at Maritime Continent. In this study, using principal oscillation pattern (POP) analysis on the combined fields of daily equatorial convection and zonal wind, two distinct leading TISV modes with relatively slower e-folding decay rates are identified. One is an oscillatory mode with the period of 51 days and e-folding time of 19 days, capturing the eastward propagating (EP) feature of the canonical MJO. The other is a non-oscillatory damping mode with e-folding time of 13.6 days, capturing a standing dipole (SD) with convection anomalies centered over the Maritime Continent and tropical central Pacific, respectively. Compared to the EP mode, the leading moisture anomalies at low level to the east of convection center are diminish for the SD mode, and instead, the strong negative anomalies of moisture and subsidence motion emerge in the tropical central Pacific area, which may be responsible for the distinct propagation features. Without filtering methods used, timeseries of the two POPs could be applied to the real-time monitoring of EP and SD events in the phase-space diagram. The two modes can serve as the simple and objective approach for a better characterization for diverse natures of TISV beyond the canonical MJO description, which may further shed light on dynamics of the TISV and its predictability.

Impact of Deforestation in the Maritime Continent on the Madden–Julian Oscillation

Abstract Deforestation is a major issue affecting both regional and global hydroclimates. This study investigated the effect of deforestation in the Maritime Continent (MC) on tropical intraseasonal climate variability. Using a global climate model with credible Madden–Julian oscillation (MJO) simulations, we examined the effect of deforestation over the MC region by replacing the forest canopy with grassland. The results revealed that under constant orographic and land–sea contrast forcing, the modification of the canopy over the MC altered the characteristics of the MJO. We noted the amplification of the MJO and increases in wet–dry fluctuation and the zonal extent. We analyzed more than 100 MJO cases by performing K-means clustering and determined that the continuous propagation of the MJO over the MC increased from 35% in the control experiment to 61% in the deforestation experiment. This phenomenon of less blocked MJO over the MC in the deforestation run was associated with more substantial precipitation, increased soil moisture, and a suppressed diurnal cycle in land convection. Furthermore, when the MJO convection was over the Indian Ocean (IO), we observed the enhancement of low-level moisture over the MC region in the deforestation experiment. Grassland surface forcing provides a thermodynamic source for triggering instability in the atmosphere, resulting in low-level moisture convergence. The MJO exhibited a stronger energy recharge–discharge cycle in the deforestation experiment than in the control experiment, and this difference between the experiments enlarged as the MJO progressed from the IO to MC.

Deep learning reveals moisture as the primary predictability source of MJO

The Madden-Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability that interacts with many other Earth system phenomena. The prediction skill of the MJO in many operational models is lower than its potential predictability, partly due to our limited understanding of its predictability source. Here, we investigate the source of MJO predictability by combining machine learning (ML) with a 1200-year-long Community Earth System Model version 2 (CESM2) simulation. A Convolutional Neural Network (CNN) for MJO prediction is first trained using the CESM2 simulation and then fine-tuned using observations via transfer learning. The source of MJO predictability in the CNN is examined via eXplainable Artificial Intelligence (XAI) methods that quantify the relative importance of the input variables. Our CNN exhibits an enhanced prediction skill over previous ML models, achieving a skill level of about 25 days. This level of performance is slightly superior or comparable to most operational models participating in the S2S project, although a few dynamical models surpass it. The XAI methods highlight precipitable water anomalies over the Indo-Pacific warm pool as the primary precursors of the subsequent MJO development for 1–3 weeks forecast lead times. Our results suggest that realistic representation of moisture dynamics is crucial for accurate MJO prediction.

Identification of the Madden–Julian Oscillation With Data‐Driven Koopman Spectral Analysis

AbstractThe Madden‐Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, is commonly identified using the realtime multivariate MJO (RMM) index based on joint empirical orthogonal function (EOF) analysis of near‐equatorial upper and lower level zonal winds and outgoing longwave radiation. Here, in place of conventional EOFs, we apply an operator‐theoretic formalism based on dynamic systems theory (the Koopman operator) to extract an analog to RMM that exhibits certain features that refine the characterization and predictability of the MJO. In particular, the spectrum of Koopman operator eigenfunctions, with eigenvalues corresponding to mode periods, contains a leading intraseasonal mode with period of ∼50 days. Moreover, the amplitude of this leading intraseasonal eigenfunction exhibits a seasonal modulation clearly peaked in boreal winter. Finally, the phase space formed by the complex Koopman MJO eigenfunction exhibits a smoother temporal evolution and higher degree of autocorrelation than RMM, which may contribute to enhanced predictive skill.

Low-Frequency Variability in the Real-Time Multivariate MJO Index: Real or Artificial?

Abstract The real-time multivariate Madden–Julian oscillation (MJO) (RMM) index has now been widely applied as a standard in operational subseasonal prediction and monitoring. Its calculation procedures involve the extraction of major intraseasonal variability (ISV) by subtracting the prior 120-day mean. However, this study uncovers that such a real-time strategy artificially creates unwanted low-frequency variability (LFVartificial) that might cause nonnegligible influences on the RMM amplitude and phase. Compared to the real LFV, the LFVartificial explains more (∼70% in boreal summer) of the residual LFV (LFVresidual) in the RMM index. It occupies 33% of all days that the LFVresidual explains more than one-half of total RMM amplitude, 19% that the LFV contribution exceeds ISV, and 10% that the LFVartificial-associated RMM amplitude surpasses 0.8. The RMM-defined “MJO” is obscured by the LFVresidual in such a way that the eastward-propagating mode is stronger and bigger with a slower phase speed, as compared with the “true” MJO derived from the 20–100-day filtered data. The interference effects of LFVresidual on the MJO might be particularly strong when the background state is changing rapidly with time. However, these issues can be well avoided when one chooses to remove the centered 120-day mean, as evidenced by the largely reduced three percentages (17%, 8%, and 1%) mentioned above in the so-derived index. These results give us a reminder that more attention should be paid to monitoring or predicting an MJO using the RMM index in a rapidly changing low-frequency background or in the boreal summer. Significance Statement The real-time multivariate MJO (RMM) index has been widely applied in the monitoring and prediction of the MJO, the major tropical intraseasonal variability influencing global weather and climate. Using observational analysis, we reveal that there exist such scenarios (∼16%) when large-amplitude RMM indices do not represent a strong MJO, mainly due to the obscuring effect of residual, while largely artificial, low-frequency variability introduced by the RMM calculation procedures. This finding is of great significance as it informs the research community that serious caution should be given when relating large RMM amplitude to the MJO, especially in a condition when the low-frequency background state is rapidly changing with time or in the boreal summer.

European heatwaves: Link to large‐scale circulation patterns and intraseasonal drivers

AbstractThis study examines the European heatwaves' predictability at subseasonal timescales. Land surface feedbacks and tropical convection, due to their variability at intraseasonal timescales, are taken into consideration and their potential role in extending the predictability beyond the medium range (10 days) is explored. A classification of European heatwaves into five heatwave types is used to discriminate the effects of surface feedbacks and of tropical variability among the different heatwave types. The classification is computed in terms of circulation patterns. By inferring the near‐surface temperature through atmospheric circulation, we aim to identify the predictable component of the heatwave events. All five heatwave circulation patterns are characterized by persistent anticyclonic anomalies located over the region with maximum temperatures. We show that soil moisture deficit is not a required precondition for the occurrence of heatwaves over most of Europe. However, heatwave events over southern Europe exhibit some sensitivity to dry conditions. We use a simplified index to describe the dominant mode of tropical convection at intraseasonal timescales. The index, based on precipitation anomalies, represents the evolution of the Boreal Summer Intraseasonal Oscillation (BSISO). We find that episodes with strong BSISO amplitudes characterized by enhanced convection over India, Bay of Bengal and China sea favour the occurrence of heatwave events over Russia. The results highlight the role of tropical intraseasonal variability in enhancing the predictability of some extreme temperature events over Europe.

Climatological diagnostics and subseasonal‐to‐seasonal predictions of Madden–Julian Oscillation events

AbstractThe Madden–Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability, which serves as a primary source of subseasonal‐to‐seasonal (S2S) predictability. Noticeably, MJO is not always a regularly recurring cycle but is characterized by discrete episodes. In this study, considering the quasi‐consecutive actives and eastward propagating features, a standard metric is proposed to identify MJO events based on the real‐time multivariate MJO (RMM) index. The re‐identification of historical MJO events reveals that there were 5.4 MJO events each year since 1981, and the average duration of each event is about 31.5 days. More MJO events tend to occur in the boreal winter and spring, with stronger intensity, longer duration and faster propagating speed than those in the boreal summer. Furthermore, MJO events are more likely to initiate in Phases 2 and 5, with a longer lifetime than those initiating in other phases. The amplitude and propagation characteristics of MJO events are strongly modulated by the dominant modes of sea surface temperature interannual variability with a strong regional dependence. Based on hindcast datasets of six S2S models, the prediction skill for the MJO is evaluated in the perspective of individual events. The longest leading time of the skilful prediction for individual MJO events ranges from 11 to 17 days, far below the traditional recognition. This result could be attributed to the apparent prediction barrier of MJO initiation, that is, a rapid decrease in prediction skill when predictions are carried out before the initiation of MJO events. In addition, the prediction skills of MJO events depends on interannual variabilities, with relatively higher skills under the conditions of the El Niño and Indian Ocean basin warming. These findings may shed light on the complexity and challenges of profoundly understanding and skilfully predicting MJO events.

Tropical Intraseasonal Variability Response to Zonally Asymmetric Forcing in an Idealized Moist GCM

Abstract The tropical intraseasonal variability in an idealized moist general circulation model (GCM) coupled to a slab ocean is investigated. The model has a simple moist convection scheme and realistic radiative transfer, but no parameterization of cloud processes. In a zonally symmetric aquaplanet state, variability is dominated by westward-propagating Rossby waves. Enforcing zonal asymmetry through the application of a prescribed ocean heat flux in the bottom boundary leads to the development of a slow, eastward propagating mode that bears some of the characteristics of the observed Madden–Julian oscillation (MJO). When the ocean heat flux is made stronger, high-frequency Kelvin waves exist alongside the MJO mode. The strength of the disturbances and the spatial distribution of their precipitation anomalies are sensitive to the strength of intraseasonal sea surface temperature (SST) anomalies. The greatest resemblance to the MJO is observed when shallow slab ocean depths (1 m) are used, but the mode still exists at deeper slabs. Sensitivity experiments to the parameters of the convection scheme suggest that the simulated MJO mode couples to convection in a way that is distinct from both Kelvin and Rossby waves generated by the model. Analysis of the column moist static energy (CMSE) budget of the MJO mode suggests that column radiative heating plays only a weak role in destabilizing the mode relative to the stabilizing contribution of vertical advection. The CMSE budget analysis highlights the importance of the life cycle of horizontal advection for the destabilization and propagation of the MJO. Synergies between the generated MJO mode and linear theories of the MJO are discussed as well.

Distinct MJOs Under the Two Types of La Niña

AbstractEl Niño‐Southern Oscillation (ENSO) strongly influences the interannual variations of Madden‐Julian Oscillation (MJO)—the dominant mode of tropical intraseasonal variability. Previous studies have revealed more about the impacts of the diversified El Niño on MJO, but less about those of the La Niña diversity. Using observations and global climate model experiments, this study demonstrates that MJO undergoes distinct variations and Pacific teleconnections when La Niña varies between eastern‐Pacific (EP) and central‐Pacific (CP) types. Compared to the CP La Niña, MJO under the EP La Niña is more energetic over the southern Maritime Continent–South Pacific Convergence Zone and can propagate faster and further with a broader zonal circulation scale over the Indo‐Pacific warm pool. The stronger and faster MJO under the EP La Niña is associated with more vigorous ascending motions, higher moisture content and stronger moistening in the lower‐level atmosphere ahead of the MJO deep convection. Although the meridional moisture advection exists as the fundamental mechanism of MJO eastward propagation, the distinct MJO under the two types of La Niña primarily results from the different lower‐tropospheric moistening due to the zonal moisture advection. Both the background mean and anomalous zonal winds and moisture gradients are stronger under the EP La Niña, thereby causing a remarkable invigoration effect of zonally advective moistening. Diverse extratropical circulation responses of distinct MJOs are also discussed. These results should improve our understanding of the whole ENSO diversity paradigm that influences MJO and teleconnections.

Ensemble Kalman filter based data assimilation for tropical waves in the MJO skeleton model

AbstractThe Madden–Julian oscillation (MJO) is the dominant component of tropical intraseasonal variability, with wide‐reaching impacts even on extratropical weather and climate patterns. However, predicting the MJO is challenging. One reason is the suboptimal state estimates obtained with standard data assimilation (DA) approaches. These are typically based on filtering methods with Gaussian approximations and do not take into account physical properties that are important specifically for the MJO. In this article, a constrained ensemble DA method is applied to study the impact of different physical constraints on the state estimation and prediction of the MJO. The quadratic programming ensemble (QPEns) algorithm utilized extends the standard stochastic ensemble Kalman filter (EnKF) with specifiable constraints on the updates of all ensemble members. This allows us to recover physically more consistent states and to respect possible associated non‐Gaussian statistics. The study is based on identical twin experiments with an adopted nonlinear model for tropical intraseasonal variability. This so‐called skeleton model succeeds in reproducing the main large‐scale features of the MJO and closely related tropical waves, while keeping adequate simplicity for fast experiments on intraseasonal time‐scales. Conservation laws and other crucial physical properties from the model are examined as constraints in the QPEns. Our results demonstrate an overall improvement in the filtering and forecast skill when the model's total energy is conserved in the initial conditions. The degree of benefit is found to be dependent on the observational setup and the strength of the model's nonlinear dynamics. It is also shown that, even in cases where the statistical error in some waves remains comparable with the stochastic EnKF during the DA stage, their prediction is improved remarkably when using the initial state resulting from the QPEns.

Excitation of the Madden–Julian Oscillation in Atmospheric Adjustment to Equatorial Heating

AbstractWe study the adjustment of the tropical atmosphere to localized surface heating using a Lagrangian atmospheric model (LAM) that simulates a realistic Madden–Julian oscillation (MJO)—the dominant, eastward-propagating mode of tropical intraseasonal variability modulating atmospheric convection. Idealized warm sea surface temperature (SST) anomalies of different aspect ratios and magnitudes are imposed in the equatorial Indian Ocean during MJO-neutral conditions and then maintained for 15 days. The experiments then continue for several more months. Throughout these experiments, we observe a robust generation of an MJO event, evident in precipitation, velocity, temperature, and moisture fields, which becomes a key element of atmospheric adjustment along with the expected Kelvin and Rossby waves. The MJO circulation pattern gradually builds up during the first week, and then starts to propagate eastward at a speed of 5–7 m s−1. The upper-level quadrupole circulation characteristic of the MJO becomes evident around day 14, with two anticyclonic gyres generated by the Gill-type response to convective heating and two cyclonic gyres forced by the excited Kelvin waves and extratropical Rossby wave trains. A moisture budget analysis shows that the eastward propagation of the MJO is controlled largely by the anomalous advection of moisture and by the residual between anomalous moisture accumulation due to converging winds and precipitation. The initial MJO event is followed by successive secondary events, maintaining the MJO for several more cycles. Thus, this study highlights the fundamental role that the MJO can play in the adjustment of the moist equatorial atmosphere to localized surface heating.

Atmospheric Rivers over the Indo-Pacific and its Associations with Boreal Summer Intraseasonal Oscillation

AbstractRecent works have revealed that the wintertime atmospheric river (AR) activity is closely related to the 30–60-day tropical intraseasonal variability, yet it remains unclear whether summertime AR activity is also significantly influenced by the intraseasonal variability, often referred to as the boreal summer intraseasonal oscillation (BSISO). Diagnosing the 40-year (1979–2018) ERA5 reanalysis dataset, the present study examines the climatological features of ARs over the Indo-Pacific region during June to October and its associations with the BSISO. Results suggest that the western North Pacific Subtropical High (WNPSH) provides a favorable circulation background for the summertime AR activity, which conveys the moisture from the tropics to midlatitude North Pacific along its periphery. Our analysis reveals that the BSISO has substantial impacts on the occurrence and distribution of ARs. More ARs are found over the western North Pacific (WNP) when the BSISO convective envelope propagates northward to the subtropical regions, while fewer ARs can be seen when convection is suppressed there. Specifically, in phases 7–8, the active BSISO convection over the Philippine Sea induces a low-pressure anomaly and the corresponding anomalous cyclonic circulation, leading to the enhanced poleward moisture transport and more frequent AR activity over the WNP. Moreover, the WNP ARs tend to be longer and have larger sizes during these two phases. It is also found that more frequent occurrence of tropical cyclones in phases 7–8 can significantly enhance the moisture transport and AR occurrence over the WNP.

Mechanism for the Spatial Pattern of the Amplitude Changes in Tropical Intraseasonal and Interannual Variability under Global Warming

AbstractThis study investigates what forms the spatial pattern of the amplitude changes in tropical intraseasonal and interannual variability—represented by the two most important variables, precipitation (ΔP′) and circulation (Δω′)—under global warming, based on 24 models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5). Diagnostic analyses reveal that the moisture budget and thermodynamic energy equations related to the ΔP′ and Δω′ proposed separately in previous studies are simultaneously tenable. As a result, we investigate the mechanism for the spatial pattern of Δω′ from the perspective of the moist static energy (MSE) balance mainly considering the positive contribution from vertical advection. Therefore, based on the simplified MSE balance, the spatial pattern of Δω′ can be approximately projected based on three factors: background circulation variability ω′, the vertical gradient of mean-state MSE , and its future change . Under global warming, the middle-level vertical gradient of MSE increases slightly over the Indian Ocean and the Maritime Continent and decreases over the equatorial Pacific where the increase in sea surface temperature (SST) exceeds the tropical mean. The vertical gradient of mean-state MSE is modified by the increase in vertical gradients of moisture and dry static energy (DSE) simultaneously. In short, the change in the vertical gradient of mean-state MSE under global warming can influence the moisture budget and thermodynamic energy balances, resulting in the spatial pattern of ΔP′ and Δω′ at intraseasonal and interannual time scales consequently, mainly determined by the lower boundary moisture condition in the response of the SST change pattern.

The four regional varieties ofSouth Asianmonsoon low‐pressure systems and their modulation by tropical intraseasonal variability

South Asian monsoon low-pressure systems (LPSs) are synoptic-scale cyclonic vortices that produce substantial precipitation over the Indian subcontinent. In this study, a catalogue of four regional varieties of LPSs, which occur during June–September 1979–2018, is used for 4 examining the track statistics, thermal and moisture structure, and precipitation contribution of each variety. The modulation of LPS activity by tropical intraseasonal variability, which is commonly monitored by the Boreal Summer Intraseasonal Oscillation, Monsoon Intraseasonal Oscillation and Madden-Julian Oscillation indices, is investigated.

Predictable Mode of Tropical Intraseasonal Variability in Boreal Summer

AbstractThis work uses a 19-yr ensemble hindcast of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the average predictable time (APT) method to detect the most predictable tropical intraseasonal variability (ISV) mode. The first and most predictable mode (APT1) of tropical ISV is similar to a joint merger of the two Madden–Julian oscillation (MJO) modes with more weight on the second mode and is characterized by a tripole pattern with two positive centers in the equatorial western Indian Ocean and central Pacific Ocean and a negative center over the Maritime Continent. The APT1 doubles the skillful prediction period made by the MJO defined by a correlation skill of 0.5 (approximately 25 days in the ECMWF model), demonstrating its potential to become a skillful prediction target and to offer powerful subseasonal prediction sources. The underlying physical process and predictability source of the APT1 are further analyzed. The APT1 is very similar to the pattern triggered by the most predictable tropical intraseasonal sea surface temperature (SST) anomalies mode, suggesting its oceanic origin. Tropical ocean–atmosphere interaction plays a critical role in the APT1 by enhancing the evolution of tropical convection cells under WES (wind–evaporation–SST) and Bjerknes feedbacks. The internal atmospheric processes also have an important impact on the formation and maintenance of the APT1.

Intraseasonal Vertical Cloud Regimes Based on CloudSat Observations over the Tropics

This study identifies the evolution of tropical vertical cloud regimes (CRs) and their associated heating structures on the intraseasonal time scales. Using the cloud classification retrievals of CloudSat during boreal winter between 2006 and 2017, the CR index is defined as the leading pair of the combined multivariate empirical orthogonal functions of the daily mean frequency of deep, high, and low clouds over the tropical Indian Ocean, Maritime Continents, and the Western Pacific. The principal components of the CR index exhibit robust temporal variance in the 30 to 80 day intraseasonal band. Based on the propagation stages of the CRs, the coherent vertical structures of cloud composition and large-scale moisture and vertical motion exhibit a westward-tilted structure. The associated Q1-QR diabatic heating and cloud radiative forcing are consistent with the key characteristics of the Madden Julian Oscillation (MJO) documented in the previous studies. Lastly, an MJO case study showcases that the presented approach characteristically captures the propagation of moisture, cloud vertical structure, and precipitation activity across spatial and temporal scales. The current results suggest that the CR index can potentially serve as an evaluation metric to cloud-associated processes in the simulated tropical intraseasonal variability in global climate models.

The CNRM Global Atmosphere Model ARPEGE‐Climat 6.3: Description and Evaluation

AbstractThe present study describes the atmospheric component of the sixth‐generation climate models of the Centre National de Recherches Météorologiques (CNRM), namely, ARPEGE‐Climat 6.3. It builds up on more than a decade of model development and tuning efforts, which led to major updates of its moist physics. The vertical resolution has also been significantly increased, both in the boundary layer and in the stratosphere. ARPEGE‐Climat 6.3 is now coupled to the new version (8.0) of the SURFace EXternalisée (SURFEX) surface model, in which several new features (e.g., floodplains, aquifers, and snow processes) improve the water cycle realism. The model calibration is discussed in depth. An amip‐type experiment, in which the sea surface temperatures and sea ice concentrations are prescribed, and following the CMIP6 protocol, is extensively evaluated, in terms of climate mean state and variability. ARPEGE‐Climat 6.3 is shown to improve over its previous version (5.1) by many climate features. Major improvements include the top‐of‐atmosphere and surface energy budgets in their various components (shortwave and longwave, total and clear sky), cloud cover, near‐surface temperature, precipitation climatology and daily‐mean distribution, and water discharges at the outlet of major rivers. In contrast, clouds over subtropical stratocumulus decks, several dynamical variables (sea level pressure, 500‐hPa geopotential height), are still significantly biased. The tropical intraseasonal variability and diurnal cycle of precipitation, though improved, remained area of concerns for further model improvement. New biases also emerge, such as a lack of precipitation over several tropical continental areas. Within the CMIP6 context, ARPEGE‐Climat 6.3 is the atmospheric component of CNRM‐CM6‐1 and CNRM‐ESM2‐1.

The Role of Extratropical Background Flow in Modulating the MJO Extratropical Response

AbstractThe Madden–Julian oscillation (MJO) is the dominant mode of tropical intraseasonal variability. Many studies have found that the MJO, which acts as a tropical heating source, can excite Rossby waves that propagate into the midlatitude and modulate midlatitude circulation. The extratropical mean flow can modulate the MJO extratropical response. Rossby waves can grow or decay in different extratropical background flows, and the propagation of the Rossby waves also varies as the background flow acts as a waveguide. In this study, how extratropical mean flow modulates the MJO extratropical response is explored by using a nonlinear baroclinic primitive equation model. MJO-associated heating, as an external forcing of the model, is imposed into scenarios with different extratropical background flows. Different background flow modulates the generation and advection of the vorticity anomalies induced by the MJO, which determines the initial location and strength of the Rossby waves. The midlatitude waveguides can be different as the background flow changes. As the propagation of Rossby waves follows the waveguides, the background flow determines whether the Rossby waves are trapped in the Pacific Ocean region or can propagate to the north and to the east into North America. The experiments also show that the anomalies associated with the Rossby waves can extract energy from the midlatitude jet over the jet exit region and the southern flank of the jet. This further modulates the strength, location, and duration of the MJO extratropical response.

The Role of MJO Propagation, Lifetime, and Intensity on Modulating the Temporal Evolution of the MJO Extratropical Response

AbstractThe Madden‐Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability. Many studies have found that the MJO has significant impacts on extratropical weather. Since the MJO can act as a tropical heat source that excites Rossby waves, midlatitude weather is modulated by the MJO due to the Rossby waves that propagate into the midlatitude and modulate the midlatitude circulation. Heat sources of individual MJO events are different since each event has different eastward propagation speed, lifetime, intensity, and structure. The background flow is also different for each event. These result in different Rossby waves and different extratropical response for each MJO event. In this study, the role of MJO propagation speed, lifetime, and intensity on modulating the structure and temporal evolution of the MJO extratropical response is systematically explored by using an idealized general circulation model. By adding the MJO‐associated heating into the general circulation model as an external forcing, the extratropical response in the Reanalysis is captured reasonably by the model. However, large ensemble model simulations show that the response in the Reanalysis is not robust. Experiments with MJO events of different propagation speed, lifetime, and intensity show that to excite a strong extratropical response, the MJO has to propagate through specific phases (Phases 1–3 and 5–7). The intensity, timing, and duration of the extratropical response strongly depend on when the MJO is initiated and when the MJO decays. The extratropical impacts of slow‐ and fast‐propagating MJO also have significant differences, especially on intensity and duration.

Moist Entropy and Water Isotopologues in a Zonal Overturning Circulation Framework of the Madden‐Julian Oscillation

AbstractThe Madden‐Julian oscillation (MJO) is the principal source of tropical intraseasonal variability, yet challenges remain to accurately simulate its observed convective behavior and eastward propagation. There is specific need for evaluating the role of water within the MJO, including evaporation, vertical transport, precipitation, and latent heating of the coupled atmosphere‐ocean system. Hydrogen isotope ratios are particularly useful for investigating these aspects of the water cycle. This study complements previous characterization of MJO joint distributions for water vapor and isotopologue concentrations (δD) with consideration of moist entropy in the tropical zonal overturning circulation framework of the MJO. The goals are to distinguish the roles of convective and large‐scale dynamic processes through the life cycle of the MJO and identify shortcomings for modeling MJO humidity, clouds, and convection. From MJO composite analyses, wet equivalent potential temperature (θq) anomalies are largest at 500 hPa and tilt westward with altitude. A positive θq anomaly co‐occurs with the precipitation maxima, and negative θq anomalies co‐occur with subsidence both trailing and leading the convective center. Out of phase with θq, δD anomalies are positive east and negative west of the convective center, coherent with the regional zonal overturning stream function. These results point to a decoupling in the MJO between midtroposphere water vapor, which is tied to convective processes, and the isotopologue ratios, which are tied to the large‐scale circulation. A conceptual model is presented to describe the physical processes that explain the MJO life‐cycle for joint distributions of humidity (q) and water vapor δD.