Real-time Multivariate Madden–Julian Oscillation Index Research Articles

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.

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.

Assessing the Impact of Ocean In Situ Observations on MJO Propagation Across the Maritime Continent in ECMWF Subseasonal Forecasts

AbstractDespite the well‐recognized initial value nature of the subseasonal forecasts, the role of subsurface ocean initialization in subseasonal forecasts remains underexplored. Using observing system experiments, this study investigates the impact of ocean in situ data assimilation on the propagation of Madden–Julian Oscillation (MJO) events across the Maritime Continent in the European Centre for Medium‐Range Weather Forecasts (ECMWF) subseasonal forecast system. Two sets of twin experiments are analyzed, which only differ on the use or not of in situ ocean observations in the initial conditions. Besides using the Real‐time Multivariate MJO Index (RMMI) to evaluate the forecast performance, we also develop a new MJO tracking method based on outgoing longwave radiation anomalies (OLRa) for forecast evaluation. We find that the ocean initialization with in situ data assimilation, though having an impact on the forecasted ocean mean state, does not improve the relatively low MJO forecast skill across the Maritime Continent. Moist static energy budget analysis further suggests that a significant underestimation in the meridional moisture advection in the model forecast may hinder the potential role played by the ocean state differences associated with data assimilation. Bias of the intraseasonal meridional winds in the model is a more important factor for such underestimation than the mean state moisture biases. This finding suggests that atmospheric model biases dominate the forecast error growth, and the atmospheric circulation bias is one of the major sources of the MJO prediction error and should be a target for improving the ECMWF subseasonal forecast model.

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.

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.

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.

Impacts of the Madden-Julian Oscillation (MJO) on rainfall in Sri Lanka

The influence of the Madden Julian Oscillation (MJO) on rainfall in Sri Lanka (SL) is examined based on 30 years of daily station data from 1981-2010. Composites are constructed for each of the eight phases of the MJO defined with the Real-time Multivariate MJO (RMM) index, using daily rainfall data from 44 stations over SL for four climatic seasons and comparing to similar results from a satellite-based rainfall product. Composites of lower tropospheric wind and convective anomaly are also investigated in order to examine how the local rainfall anomalies are associated with large-scale circulations. The greatest impact of the MJO on rainfall over SL occurs in the Second Inter-Monsoon (SIM) and Southwest Monsoon (SWM) seasons. Enhanced rainfall generally occurs over SL during RMM phases 2 and 3 when the MJO convective envelop is located in the Indian Ocean and conversely suppressed rainfall in phases 6 and 7. This rainfall impact is due to the direct influence of the MJO’s tropical convective anomalies and associated low-level circulations in the vicinity of SL. In contrast, the MJO influence during the Northeast Monsoon (NEM) season is slightly less than during the SWM and SIM seasons as a result of the southward shift of the MJO convective envelop during boreal winter. Occurrence of extreme rainfall events is most frequent during phase 2 in First Inter-Monsoon (FIM) phases 2 and 3 in SWM, phases 1, 2 and 3 in SIM and phases 2 and 3 in NEM seasons. The analysis of this study provides a useful reference of when and where the MJO has significant impacts on rainfall as well as extreme rainfall events during four climatic seasons in SL. This information can be used along with accurately predicted MJO phase by dynamical or statistical models, to improve extended range forecasting in SL.

Potential predictability of the MJO during easterly and westerly phases of the QBO

The potential predictability of the Madden–Julian Oscillation (MJO) in boreal winter (November–February) is investigated using observational data for the period of 1979–2016. For various MJO indices, nonlinear local Lyapunov exponents are computed to quantify the MJO predictability under the easterly and westerly phases of the Quasi-Biennial Oscillation (easterly: EQBO and westerly: WQBO). All MJO indices exhibit higher predictability during EQBO winters than during WQBO winters. Excluding strong ENSO years from EQBO and WQBO winters has a limited impact on MJO predictability. The highest potential predictability of 43 days during EQBO winters and 37 days during WQBO winters is found for the MJO index obtained from bandpass-filtered (30–80 days) outgoing longwave radiation and wind data. In contrast, the potential predictability of the MJO from the real-time multivariate MJO index is 21 days during EQBO winters and 13 days during WQBO winters. The longer persistence and less disorganization of the MJO during the EQBO winters lead to the higher predictability for EQBO winters, as compared with that for WQBO winters.

Formation of Nocturnal Offshore Rainfall near the West Coast of Sumatra: Land Breeze or Gravity Wave?

AbstractAfternoon deep convection over the Maritime Continent islands propagates offshore in the evening to early morning hours, leading to a nocturnal rainfall maximum over the nearby ocean. This work investigates the formation of the seaward precipitation migration off western Sumatra and its intraseasonal and seasonal characteristics using BMKG C-band radar observations from Padang and ERA5 reanalysis. A total of 117 nocturnal offshore rainfall events were identified in 2018, with an average propagation speed of 4.5 m s−1 within 180 km of Sumatra. Most offshore propagation events occur when the Madden–Julian oscillation (MJO) is either weak (real-time multivariate MJO index < 1) or active over the Indian Ocean (phases 1–3), whereas very few occur when the MJO is active over the Maritime Continent and western Pacific Ocean (phases 4–6). The occurrence of offshore rainfall events also varies on the basis of the seasonal evolution of the large-scale circulation associated with the Asian–Australian monsoons, with fewer events during the monsoon seasons of December–February and June–August and more during the transition seasons of March–May and September–November. Low-level convergence, resulting from the interaction of the land breeze and background low-level westerlies, is found to be the primary driver for producing offshore convective rain propagation from the west coast of Sumatra. Stratiform rain propagation speeds are further increased by upper-level easterlies, which explains the faster migration speed of high reflective clouds observed by satellite. However, temperature anomalies associated with daytime convective latent heating over Sumatra indicate that gravity waves may also modulate the offshore environment to be conducive to seaward convection migration.

Diversity of the Global Teleconnections Associated with the Madden–Julian Oscillation

AbstractA recent study has revealed that the Madden–Julian oscillation (MJO) during boreal winter exhibits diverse propagation patterns that consist of four archetypes: standing MJO, jumping MJO, slow eastward propagating MJO, and fast eastward propagating MJO. This study has explored the diversity of teleconnection associated with these four MJO groups. The results reveal that each MJO group corresponds to distinct global teleconnections, manifested as diverse upper-tropospheric Rossby wave train patterns. Overall, the teleconnections in the fast and slow MJO are similar to those in the canonical MJO constructed by the real-time multivariate MJO (RMM) indices, while the teleconnections in the jumping and standing MJO generally lose similarities to those in the canonical MJO. The causes of this diversity are investigated using a linearized potential vorticity equation. The various MJO tropical heating patterns in different MJO groups are the main cause of the diverse MJO teleconnections, as they induce assorted upper-level divergent flows that act as Rossby-wave sources through advecting the background potential vorticity. The variation of the Asian jet could affect the teleconnections over the Pacific jet exit region, but it plays an insignificant role in causing the diversity of global teleconnections. The numerical investigation with a linear baroclinic model shows that the teleconnections can be interpreted as linear responses to the MJO’s diabatic heating to various degrees for different MJO groups, with the fast and slow MJO having higher linear skill than the jumping and standing MJO. The results have broad implications in the MJO’s tropical–extratropical interactions and the associated impacts on global weather and climate.

Exploring the long-term changes in the Madden Julian Oscillation using machine learning

The Madden Julian Oscillation (MJO), the dominant subseasonal variability in the tropics, is widely represented using the Real-time Multivariate MJO (RMM) index. The index is limited to the satellite era (post-1974) as its calculation relies on satellite-based observations. Oliver and Thompson (J Clim 25:1996–2019, 2012) extended the RMM index for the twentieth century, employing a multilinear regression on the sea level pressure (SLP) from the NOAA twentieth century reanalysis. They obtained an 82.5% correspondence with the index in the satellite era. In this study, we show that the historical MJO index can be successfully reconstructed using machine learning techniques and improved upon. We obtain a significant improvement of up to 4%, using the support vector regressor (SVR) and convolutional neural network (CNN) methods on the same set of predictors used by Oliver and Thompson. Based on the improved RMM indices, we explore the long-term changes in the intensity, phase occurrences, and frequency of the winter MJO events during 1905–2015. We show an increasing trend in MJO intensity (22–27%) during this period. We also find a multidecadal change in MJO phase occurrence and periodicity corresponding to the Pacific Decadal Oscillation (PDO), while the role of anthropogenic warming cannot be ignored.

An Index Intercomparison for MJO Events and Termination

AbstractThe Madden‐Julian oscillation (MJO) is a significant contributor to climate variability in the tropics. While many studies have examined the MJO, few have considered its termination. Multiple indices exist to track and forecast the MJO although the influence of each index on MJO decay has not been documented. This study presents an intercomparison of several MJO indices for a 34‐year period to examine the evolution of MJO events and comprises an index‐specific climatology for MJO termination. We present an analysis of common indices including the OLR‐based MJO index (OMI) and filtered OMI (FMO) in addition to the real‐time multivariate MJO (RMM) and velocity potential MJO (VPM) index. Normalized empirical orthogonal function comparisons reveal only minor shifts in longitude and time in the corresponding convection and circulation anomalies between indices. The daily rate‐of‐change (ROC) for each index is derived, and we find that the RMM and VPM indices experience twice as large of daily amplitude changes as the univariate indices. Results from the ROC analysis are implemented in an MJO event identification algorithm to study the sensitivity of MJO termination to changes in the temporary minimum amplitude and threshold used to define events. The corresponding counts of primary, continuing, and circumnavigating events are recorded with primary events being robust to changes in the temporary minimum amplitude. Finally, an MJO climatology is created that presents MJO termination as a function of phase for each index. Physical reasons behind differences in the termination climatology are proposed in addition to applications for future work.

An Analogy toward the Real-Time Multivariate MJO Index to Improve the Estimation of the Impacts of the MJO on the Precipitation Variability over Iran in the Boreal Cold Months

In addition to the tropical data, the OLR/U850/U200 data on a restricted region in southwestern Asia (17.5°N-35°N, 30°E-60°E) has been incorporated into the calculation of the Real-time Multivariate MJO (RMM) index. Introducing this data modifies the leading EOFs of the RMM index slightly and rotates them 14° eastward as a consequence of the change in the column variances of the RMM anomaly matrix at 30°E-60°E longitudes. However, the leading principal components of the new index, which is called Regionally Modified RMM (hereafter, RM-RMM), remain approximately unchanged. Owing to this close relationship between the two indices, the 14° phase-shift is considered as a basis for comparing the influences of the intraseasonal tropics-southwestern Asia variabilities on the precipitation over Iran with those of the MJO. Accordingly, by generating the spatial patterns of the precipitation anomaly, precipitation occurrence probability and other fields based on every active phase of the RM-RMM and RMM indices, the significant differences are revealed between the corresponding phases of the two indices for the phases 1, 3, 5, 7, and 8, separately. These results ameliorate the estimation of the impacts of the MJO on the precipitation and indicate that the RM-RMM index could be used as a companion to the RMM to forecast the precipitation in Iran. Remarkably, the precipitation forecast skill of the lag-regression model based on the RM-RMM index exceeds that of the model based on the RMM for certain time lags during the phases 1, 3, 5, 7 and 8 of the two indices.