Real-time Multivariate MJO Research Articles

Impacts of the Madden‐Julian Oscillation on Marginal Sea Heatwaves of the Southeastern Tropical Indian Ocean

AbstractMarginal seas of the southeastern tropical Indian Ocean (SETIO), including the South Java coasts and the Timor and Arafura Seas, are hotspots of large‐scale marine heatwaves (MHWs) in austral summer with notable impacts on local ecosystems. Yet, the prediction of these MHWs remains challenging. By analyzing 39 MHWs and 45 marine cold‐spells (MCSs) observed in the summers of 1982–2021, this study reveals a robust modulation effect of the Madden‐Julian Oscillation (MJO) on these events. The results show that 56% of MHWs and 51% of MCSs overlapped with MJO events, and their duration is systematically longer than others. Moreover, MHWs in phases 3–4 and MCSs in phases 6–7 of the real‐time multivariate MJO (RMM) index were nearly 2–3 times stronger in intensity than the others. The passage of MJOs drives prominent intraseasonal sea surface temperature (SST) variability in the SETIO through perturbing surface heat fluxes, which in turn modulates the occurrence of MHWs and MCSs. During RMM phases 1–2 (convective center over of the east of Africa or the central‐western Indian Ocean), the SETIO is controlled by a dry condition, with increased surface insolation and suppressed latent heat release. These anomalous fluxes drive a persistent SST increase, facilitating the emergence of strong and prolonged MHWs in the subsequent RMM phases 3–4. Further analysis suggests an 18% probability for MHWs in the SETIO 12 ± 10 days after Phase 1. Therefore, the MJO contributes to the predictability of MHWs/MCSs of the SETIO, with implications for predicting climate extremes and hazards.

Intensity duration and frequency of Heat wave in different phases of MJO over India

The Madden-Julian Oscillation (MJO) is an important tropical atmospheric phenomenon that plays a significant role in modulating weather patterns across India. Heat Waves (HW) are extreme weather events that have severe impacts on human health, agriculture, and various socio-economic sectors. This research paper aims to investigate the dynamical relationship between MJO phases, as measured by the Real-time Multivariate MJO (RMM) index, and the occurrence of HW in India, as defined by the Indian Meteorological Department. This paper demonstrated the relationship among three aspects, i.e., intensity, duration, frequency of HW during the different MJO phases. The differential dynamics associated for about two-fold rise in the HW occurrence in the South East, Eastern and North West India in the MJO active phase. Inactive phase witnessed enhancement (suppression) of HW during wet (dry) over the regions. The novel finding of this paper is that, the weaker the MJO, the higher probability of HW occurrence in respective regions depending on the position of the MJO convection center. The maximum duration is observed to be significantly decreased by about 2 days in the active MJO phase over NW and north central parts of the country. It is also inferred from this study that there is a significantly decrease of 0.5 °C in HW intensity during the active wet phase of MJO over the NW India. To explain the linkage of HW with MJO, geopotential height (GPH), wind circulation, velocity potential (VP), sea surface temperature (SST) and outgoing longwave radiation (OLR) composite anomalies have been computed and used in the analysis. It is observed that all these parameters have a direct impact on the evolution, strength and spread of the HW in India. This dynamical study mechanism can be prescribed in the numerical weather prediction models for the improved prediction of such extreme weather events during summer for proactive disaster management.

The Role of Multiscale Interaction in the Maintenance and Propagation of MJO in Boreal Winter

Abstract The multiscale interaction and its role in the maintenance and propagation of the Madden–Julian oscillation (MJO) has been investigated using the newly developed multiscale window transform (MWT), the theory of canonical transfer, and the MWT-based multiscale energetics analysis (here particularly for this study, dry energetics analysis). The field variables are reconstructed/filtered with MWT onto three scale windows, namely a high-frequency window, intraseasonal window, and low-frequency window. Compositing the intraseasonal fields with respect to the real-time multivariate MJO (RMM) index unambiguously shows that the zonal extents of the easterlies and westerlies of MJO vary with the RMM phases, among which phases 4 and 2 are representative. In the former phase, the MJO has easterlies and westerlies within the same extent, while in the latter their extents are quite different. In phase 4, besides the previously discovered mechanisms such as pressure work and buoyancy conversion, the MJO is also energized by the canonical kinetic energy (KE) transfer from the low-frequency window to the intraseasonal window (signifying barotropic instability) on the west of its convection. But on the eastern side, MJO loses KE to the low-frequency window. The KE transport also functions like an energy sink. In phase 2, the MJO variabilities can be divided into an eastern part and a western part. The former is essentially the same as that in phase 4; for the latter, barotropic instability dominates. On the available potential energy (APE) budget, baroclinic instability and intraseasonal APE transport help produce and maintain the temperature anomalies. In contrast to previous energetics studies, our findings highlight the essential role played by multiscale interactions.

Stratosphere-troposphere coupling during stratospheric extremes in the 2022/23 winter

Using the ERA5 reanalysis, sea surface temperature, sea ice observations, and the real-time multivariate Madden-Julian Oscillation (MJO) index, the evolution of the stratospheric extreme circulation in the winter of 2022/2023 is explored. The stratospheric polar vortex was disturbed three times in the 2022/23 winter, contrasted with only one disturbance during the other three recent winters with an SSW. Possible favorable conditions for the strong stratospheric disturbances and their effects on stratospheric ozone, water vapor distribution, and near-surface temperature were examined. Around 7 December 2022 when a short but strong pulse of planetary wavenumber 2 appeared from the troposphere to stratosphere, a weakened and elongated stratospheric polar vortex formed at 10 hPa. This pulse is related to the intensifying Ural ridge and the deepening East Asian trough. After the first stratospheric disturbance, a large fraction of cold anomalies occurred in the Eurasian continent. A lagged impact after these stratospheric disturbances was observed as strong cold anomalies formed in North America from 13 to 23 December. On 28 January 2023, a minor SSW event occurred due to a displacement of the stratospheric polar vortex. A strong pulse of eddy heat flux contributed alternately by planetary wavenumber 1 and 2 showed a large accumulative effect on the stratospheric disturbance. However, the downward impact of this second disturbance was weak, and cold surges were not noticeable after this minor SSW. The third stratospheric disturbance this winter is a major displace-type SSW that occurred on 16 February 2023, and the total eddy heat flux primarily contributed by planetary wavenumber 1 increased rapidly. Following the major SSW, the North American continent was covered by large patches of strong cold anomalies until the end of March. During the three disturbances, the residual circulation correspondingly strengthened. The water vapor and ozone in the middle and lower layers of the polar stratosphere showed positive anomaly disturbances, especially after the major SSW onset. The unprecedented frequent stratospheric disturbances in winter 2022/23 were accompanied by severe loss of Barents-Laptev Sea ice and anomalously cold tropical Pacific sea surface temperatures (La Niña), which have been reported to be conducive to the enhancement of planetary waves 1 and 2 respectively. Further, two weeks before the major SSW, existing MJO developed into phases 4–6, also contributing to the occurrence of major SSW.

Seasonal Modulation of the Madden–Julian Oscillation’s Impact on Rainfall in Sri Lanka

Abstract For the tropical country of Sri Lanka, subseasonal variability in precipitation is both ecologically and societally relevant, influencing agricultural yields, natural hazard risk, energy production, and disease incidence. The primary driver of this subseasonal precipitation variability is the Madden–Julian oscillation (MJO). Here we investigate this influence on Sri Lankan precipitation across seasons, describing MJO-associated precipitation patterns and exploring the potential for MJO-informed subseasonal forecasts. We do so using 40-yr satellite-derived records of precipitation with high spatial resolution (from CHIRPS v2.0) and related meteorological and atmospheric fields (from ERA5 and MERRA-2). We find a direct MJO influence on precipitation corresponding to propagation of the MJO’s convectively active region and suppressed region near Sri Lanka, with the strength and spatial patterns of this influence differing across seasons. There are particularly strong impacts in the second intermonsoon (SIM; October–November) and southwest monsoon (SWM; May–September) seasons. During SIM the impacts are island-wide, but strongest in the northeast. During the SWM the absolute impacts are localized to the southwest, but the relative impacts (i.e., relative to precipitation climatology) are fairly uniform across the island. Moreover, we find significant associations between MJO phase and Sri Lankan precipitation at time scales of up to several weeks. Notably, these associations are stronger when using the OLR-based MJO index (OMI) rather than the more commonly used real-time multivariate MJO index (RMM). While the MJO associations we describe here arise from a highly simplified forecasting scheme, they provide a foundation and impetus for developing a more complete, MJO-informed precipitation forecast method. Significance Statement Rainfall variability at the subseasonal (weeks–months) time scale is critical to societal well-being, given its fundamental importance for agriculture, flood risk, hydropower generation, and disease incidence. Our work describes how such rainfall variability in Sri Lanka is impacted by the Madden–Julian oscillation, in which a region of enhanced rainfall and cloudiness, paired with a region of decreased rainfall and cloudiness, circles the globe every 30–60 days. Our results suggest that its influence on Sri Lankan rainfall may be strong enough that incorporating knowledge of the Madden–Julian oscillation into forecasts can improve the accuracy of rainfall prediction for Sri Lanka. Future work should develop a more comprehensive forecast method to assess viability in real-world forecasting scenarios.

Evaluation and Process-Oriented Diagnosis of the GEFSv12 Reforecasts

Abstract Three levels of process-oriented model diagnostics are applied to evaluate the Global Ensemble Forecast System version 12 (GEFSv12) reforecasts. The level-1 diagnostics are focused on model systematic errors, which reveals that precipitation onset over tropical oceans occurs too early in terms of column water vapor accumulation. Since precipitation acts to deplete water vapor, this results in prevailing negative biases of precipitable water in the tropics. It is also associated with overtransport of moisture into the mid- and upper troposphere, leading to a dry bias in the lower troposphere and a wet bias in the mid–upper troposphere. The level-2 diagnostics evaluate some major predictability sources on the extended-range time scale: the Madden–Julian oscillation (MJO) and North American weather regimes. It is found that the GEFSv12 can skillfully forecast the MJO up to 16 days ahead in terms of the Real-time Multivariate MJO indices (bivariate correlation ≥ 0.6) and can reasonably represent the MJO propagation across the Maritime Continent. The weakened and less coherent MJO signals with increasing forecast lead times may be attributed to humidity biases over the Indo-Pacific warm pool region. It is also found that the weather regimes can be skillfully predicted up to 12 days ahead with persistence comparable to the observation. In the level-3 diagnostics, we examined some high-impact weather systems. The GEFSv12 shows reduced mean biases in tropical cyclone genesis distribution and improved performance in capturing tropical cyclone interannual variability, and midlatitude blocking climatology in the GEFSv12 also shows a better agreement with the observations than in the GEFSv10. Significance Statement The latest U.S. operational weather prediction model—Global Ensemble Forecast System version 12—is evaluated using a suite of physics-based diagnostic metrics from a climatic perspective. The foci of our study consist of three levels: 1) systematic biases in physical processes, 2) tropical and extratropical extended-range predictability sources, and 3) high-impact weather systems like hurricanes and blockings. Such process-oriented diagnostics help us link the model performance to the deficiencies of physics parameterization and thus provide useful information on future model improvement.

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.

PM2.5 extended-range forecast based on MJO and S2S using LightGBM

We developed an extended-range fine particulate matter (PM2.5) prediction model in Shanghai using the light gradient-boosting machine (LightGBM) algorithm based on PM2.5 historical data, meteorological observational data, Subseasonal-to-Seasonal Prediction Project (S2S) forecasts and Madden-Julian Oscillation (MJO) monitoring data. The analysis and prediction results demonstrated that the MJO improved the predictive skill of the extended-range PM2.5 forecast. The MJO indexes, namely, real-time multivariate MJO series 1 (RMM1) and real-time multivariate MJO series 2 (RMM2), ranked the first, and seventh, respectively, in terms of the predictive contribution of all meteorological predictors. When the MJO was not introduced, the correlation coefficients for the forecasts on lead times of 11–40 days ranged from 0.27 to 0.55, and the root mean square errors (RMSEs) ranged from 23.4 to 31.8 μg/m3. After the MJO was introduced, the correlation coefficients for the 11–40 day forecast ranged from 0.31 to 0.56, among which those for the 16–40 day forecast substantially improved, and the RMSEs ranged from 23.2 to 28.7 μg/m3. When comparing the prediction scores, such as percent correct (PC), critical success index (CSI), and equitable threat score (ETS), the forecast model was more accurate when it introduced the MJO. A novel aspect of this study is to investigate the effects of the MJO mechanism on the meteorological conditions of air pollution in eastern China through advanced regression analysis. The MJO indexes RMM1 and RMM2 considerably impacted the geopotential height field of 28°–40° at 300–250 hPa 45 days in advance. When RMM1 increased and RMM2 decreased 45 days in advance, the 500 hPa geopotential height field weakened accordingly, and the bottom of the 500 hPa trough moved southward; thus cold air was more easily transported southward and the upstream air pollutants were transported to eastern China. With a weak ground pressure field and dry air at low altitudes, the westerly wind component increased, which led to the easier formation of a weather configuration favorable for the accumulation and transport of air pollution, thus resulting in an increase in PM2.5 concentration in the region. These findings can guide forecasters regarding the utility of MJO and S2S for subseasonal air pollution outlooks.

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.

The Indo-Pacific Maritime Continent Barrier Effect on MJO Prediction

Abstract The Madden–Julian oscillation (MJO) is often observed to weaken or sometimes completely decay as its convective anomaly moves from the Indian Ocean over to the Maritime Continent (MC), which is known as the MC barrier effect on the MJO. This barrier effect is often exaggerated in numerical models. Using 23 years of the retrospective intraseasonal forecast from two coupled model systems with useful MJO prediction skills, we show that the predictive skill of the real-time multivariate MJO (RMM) index for the continuously propagating MJO events across the MC region is higher than for the blocked MJO events. The greater prediction skill is not related to the higher initial RMM amplitude for the continuous MJO events. Rather the higher skill arises from the more persistent behavior of the propagating MJO events as the convective anomaly moves through the MC region into the western Pacific. The potential predictability is similar for both types of MJO events, suggesting the forecast models hardly differentiate the two types of MJO events in prediction; they only maintain higher RMM magnitudes of the continuously propagating events. The global reanalysis dataset indicates that the blocked events are often associated with persistent higher surface pressures over colder sea surface temperatures in the central Pacific, suggesting the large-scale environment plays a role in promoting or inhibiting the MJO propagation across the MC region. Caveats in the models to reproduce the observed MJO events are also discussed.

Madden–Julian Oscillation Impacts on Australian Temperatures and Extremes

Abstract We assess seasonally varying impacts of the Madden–Julian oscillation (MJO) on Australian maximum and minimum temperature anomalies and extremes, and their modulation by El Niño–Southern Oscillation (ENSO), for the period June 1974–May 2022. Our composite-based approach uses observed temperatures from the Australian Gridded Climate Data, and 850-hPa wind data from the NCEP–NCAR reanalysis, to show how relationships to temperature and circulation evolve over the eight-phase life cycle of the MJO, which we derive from the real-time multivariate MJO index. The MJO has significant impacts on Australian temperatures and winds in all parts of the country at various times throughout the year, and to varying degrees. Two of the most pronounced impacts are 1) daytime warming across southeastern Australia in MJO phase 3 during spring associated with a strong anomalous anticyclone and 2) nighttime cooling over Queensland in MJO phase 7 during winter associated with anomalous advection of cool dry continental air. La Niña acts to significantly lessen both of these impacts, while El Niño enhances both the phase 3 warming over southern Australia in spring and the phase 7 overnight cooling over southern Queensland in winter. We show how the MJO can combine with El Niño and La Niña to have strong compounding influences, thus highlighting the importance of understanding interactions between multiple modes of climate variability and how they relate to Australian temperatures and extremes.

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‐wave activity and Madden–Julian oscillation termination

AbstractThe Madden–Julian oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics and generates large‐scale precipitation, cloud, and circulation anomalies. Interactions between the MJO and dry and convectively coupled equatorial waves (CCEWs) have been identified in previous works; however, these studies have not focused on MJO events that maintain themselves versus those that decay. Knowledge on how pre‐existing MJO events interact with CCEWs is important for producing more realistic and reliable representations of MJO events in weather forecast and global climate models. This study presents an analysis of intraseasonally varying outgoing longwave radiation (OLR) and zonal wind anomalies at 200 and 850 hPa from National Oceanic and Atmospheric Administration (NOAA) observations and ERA‐Interim reanalysis data respectively, throughout the lifetime of observed MJO events. A climatology of continuing and terminating MJO events is created from an event identification algorithm using common tracking indices including the OLR‐based MJO Index (OMI), filtered OMI (FMO), real‐time multivariate MJO (RMM), and velocity potential MJO (VPM) index. Wheeler–Kiladis power spectra are calculated for each event type to identify predominant wave modes. Symmetric and anti‐symmetric wave spectra are composited and results include the sensitivity of the variables used to define the waves and index choice for identifying the MJO. Our results show fractional differences between continuing and terminating MJO events that are statistically significant at the 95% level. Statistical significance is most prominent within the MJO band where continuing events have higher power, as well as global mixed Rossby–gravity (MRG) waves and tropical depression (TD) waves where terminating events have higher power. These results are mostly robust to meteorological variable and index although the importance of Kelvin waves is amplified in the VPM. A regional analysis including phase separation contains results that are sensitive to variable and domain although westward traveling waves are commonly associated with MJO termination regardless of location.

The effect of the Madden–Julian Oscillation on the global electric circuit

The Madden–Julian Oscillation (MJO) is the most dominant component of the climate variability in the tropics on the timescale of tens of days. Occurring irregularly, the MJO consists of an eastward propagation of certain large-scale coupled structures in atmospheric circulation and deep convection. Here we investigate the effect of the MJO on the direct current global electric circuit (GEC), using both numerical simulations and the results of electric field measurements. We have reproduced the atmospheric dynamics for 1980–2020 with the help of the Weather Research and Forecasting model and meteorological reanalysis data; this allowed us to simulate 41 years of the GEC variation by parameterising contributions to the ionospheric potential (IP) in terms of precipitation and convection. Besides, we have analysed the results of surface potential gradient (PG) measurements at the Vostok station in Antarctica during 2006–2020. When averaged over many days, both the simulated IP and measured fair-weather PG show sinewave-like variations with the MJO phase, which manifest a statistically significant correlation with the MJO cycle. A more elaborate investigation involving an application of empirical orthogonal functions shows that the dynamics of contributions to the IP follows the patterns of variability of deep convection typical for the MJO. The variation of the IP on the MJO scale can largely be represented as a superposition of two basic oscillating patterns of convection, one of which is located over the Maritime Continent and its surrounding seas and the other is located over the Indian Ocean and part of South-East Asia. These oscillating patterns together describe the eastward progression of perturbations and can be naturally associated with the two components of the Real-time Multivariate MJO index, widely used to describe the MJO. Together with earlier results about links between the GEC and the El Niño—Southern Oscillation, the results concerning the MJO obtained in this study indicate that the GEC is an important part of the Earth system, which reflects climate variability on different timescales.

The Influence of the Madden–Julian Oscillation on the Wet Season Rainfall over Saudi Arabia

The influence of Madden–Julian oscillation (MJO) is examined on intraseasonal rainfall variability during the wet season (November–April) by using the real-time multivariate (RMM) MJO index, ERA5 reanalysis, and daily observed rainfall dataset from 26 stations in Saudi Arabia for the period 1985–2021. The MJO 8 phases are categorized into wet (phases 1, 2, 7 and 8) and dry (phases 3, 4, 5, and 6) based on the Saudi Arabian intraseasonal rainfall characteristics associated with MJO phases. It is observed that 41% (46%) of total (extreme) rainfall events occur during the MJO wet phases, while only 23% (18%) of such events occur during MJO dry phases. The intraseasonal variability signals are isolated from daily dataset by applying a 30- to 90-day period bandpass filter. The analyses are validated by constructing composites of daily filtered precipitation anomalies during MJO 8 phases. The physical mechanism indicates that the significant intraseasonal wetter conditions are linked with enhanced easterly and southeasterly moisture convergence over Saudi Arabia from the Arabian Sea. The atmospheric cyclonic circulation anomalies during the wet phases favor more moisture convergence and vertical moisture advection, which may lead to enhanced convection and rainfall. However, during the dry phases, anticyclonic circulation anomalies enhance moisture divergence and reduce vertical moisture advection and consequently suppress the convection and rainfall activity over Saudi Arabia. The analyses show that the intraseasonal rainfall variability over Saudi Arabia is significantly influenced by the MJO during the wet season. These findings have important implications for sub-seasonal rainfall forecasting in Saudi Arabia.

Impact of Madden Julian Oscillation on the diurnal cycle of precipitation over the west coast of India

Madden Julian Oscillation (MJO) is an eastward propagating convective system that passes over the Indian and Pacific Oceans with a periodicity of 30–90 days and influences most of the tropical weather systems. This study investigates and quantifies the impact of MJO on the diurnal cycle of precipitation over the west coast of India. The work uses TRMM precipitation, profiles of wind and humidity from ERA5 re-analysis and satellite Infrared window channel measurements from GridSat-B1 for the period 2000–2019. Real-time Multivariate MJO index has been used for the identification of active and suppressed MJO phases. Harmonic analysis is used to derive the diurnal and semi-diurnal amplitudes of precipitation. The active MJO phases enhance the diurnal amplitude of precipitation over the west coast with respect to the climatological diurnal cycle, whereas the suppressed phases reduce it. Active phases help in the formation of mesoscale convective cloud systems with much more spatial extension and temporal duration than that in suppressed phase. This kind of convective organization is observed especially during the active MJO phases of monsoon and post-monsoon seasons. The vertical structure of wind and humidity in the troposphere are modified by MJO where the active (suppressed) phase enhances (decreases) them. The overall modification of tropospheric dynamics, thermodynamics and deep convection by MJO can cause anomalous rainfall activity over the west coast.

Influences of MJO on the Diurnal Variation and Associated Offshore Propagation of Rainfall near Western Coast of Sumatra

Madden-Julian Oscillation (MJO) plays an important role in modulating precipitation at Maritime Continent (MC) not only on a larger scale, but also in the diurnal cycle. Diurnal rainfall offshore propagation is one of the most evident features near coasts. This study investigates the impacts of MJO on diurnal rainfall and its offshore propagation at the western coast of Sumatra during boreal winters using ERA5 reanalysis. The real-time multivariate MJO (RMM) index was applied to locate the active MJO convection through eight different phases, in the western hemisphere and Africa in P8–P1, at the Indian Ocean in P2–P3, at MC in P4–P5, and the western Pacific Ocean in P6–P7. The rainfall characteristics, including the daily rate, the absolute and normalized diurnal variation amplitudes, and the strengths of diurnal offshore propagation, not only depend on active/inactive MJO stages but also vary under different MJO phases, through the combined modulations of large-scale backgrounds and local-scale land–sea circulations. The offshore rainfall propagation is associated with meso-large-scale gravity waves generated from land–sea thermal contrast and thus is affected by the radiation effect of cloud under different MJO phases. The stronger wave signals in P8–P1 and P6–P7 enhance the diurnal rainfall variation amplitudes away from the coast, while the strong coupling of moist convection with gravity waves contributes greatly to the diurnal rainfall cycle in P2–P3.

A Multivariate Index for Tropical Intraseasonal Oscillations Based on the Seasonally‐Varying Modal Structures

AbstractThe spatial structure and propagation characteristics of tropical intraseasonal oscillations vary substantially by season. In this study, these seasonal variations are identified using a multivariate sliding‐window Empirical Orthogonal Function (EOF) analysis. The two modes comprising the leading EOF pair have equal variances and depict the propagation of intraseasonal oscillations in convection and low‐level circulation over the Indian Ocean, the Maritime Continent, and the western Pacific region in the equatorial summer hemisphere. In contrast, the upper tropospheric circulation shows more structure in the winter hemisphere. It is suggested that this variation in seasonality with height is an inherent feature of intraseasonal oscillations. A new multivariate index for tropical intraseasonal oscillations (MII) is developed based on the leading EOFs and represents the three‐dimensional structure of intraseasonal variability in all seasons. The MII is computed by projecting intraseasonal anomalies onto the leading EOFs pair, and it exhibits clearly delineated but smooth seasonal transitions and rich meridional structure. The real‐time version of this new index, rMII, is shown to be similar to MII, with a correlation of 0.9. Compared to the widely used Real‐time Multivariate MJO (RMM) index, the power spectrum of rMII represents substantially greater intraseasonal variance, and the application of rMII in dynamical forecast models indicates rMII is skillfully predicted for an additional week compared to RMM.

An Observationally Trained Markov Model for MJO Propagation

AbstractA Markovian stochastic model is developed for studying the propagation of the Madden‐Julian Oscillation (MJO). This model represents the daily changes in real time multivariate MJO (RMM) indices as random functions of their current state and background conditions. The probability distribution function of the RMM changes is obtained using a machine learning algorithm trained to maximize MJO forecast skills using observed daily indices of RMM and different modes of variability. Skillful forecasts are obtained for lead times between 8 and 27 days. Large ensemble simulations by the stochastic model show that with monsoonal changes in the background state, MJO propagation across the Maritime Continent (MC) is most likely to be disrupted in boreal spring and summer when MJO events propagate from favorable conditions over the Indian Ocean to unfavorable ones over the MC, and predictability is higher during spring and summer when MJO activity is away from the MC region.

Effect of the MJO on East Asian winter rainfall as revealed by an SVD analysis

AbstractThis paper studies the influences of the Madden Julian Oscillation (MJO) on East Asian (EA) winter rainfall using the Singular Value Decomposition (SVD) approach. This method uses two-dimensional instead of the latitudinally-averaged variables in the commonly used Real-time Multivariate MJO (RMM) index. A comparison of the two approaches is made using the same OLR and zonal wind data over 37 boreal winter seasons of December – March. The SVD composite reveals a more conspicuous and coherent variation throughout the MJO cycle, while the RMM composite is more ambiguous. In particular, the SVD analysis identifies the convection anomalies over the Maritime Continent and the subtropical western Pacific (MCWP) as a major cause of enhanced rainfall in EA at RMM phases 8 and 1. This is at least one-eighth cycle earlier than the phases of convection development over Indian Ocean (IO) that were emphasized by previous studies. A linearized global baroclinic model is used to demonstrate the mechanism of MJO forcing on EA rainfall during various phases, with a focus on the MCWP cooling. The result shows that the anomalous MCWP cooling and the resultant low-level anticyclonic flow interact with the East Asian Jet, leading to an overall weakened EA winter monsoon circulation. The associated anomalous overturning circulation, with ascending motion and low-level horizonal moisture convergence in EA, contributes to the enhanced rainfall. This model result supports the interpretation of the SVD analysis, in that the MCWP-cooling induced anomalous meridional circulation is a more direct cause of enhanced EA rainfall than the IO-heating (or the IO-MCWP heating dipole) induced Rossby wave teleconnection.