Multivariate Madden–Julian Oscillation Research Articles

The Non‐Migrating DE3 Tide Response to the MJO Phenomenon at the MLT Altitudes

AbstractBased on TIMED/SABER temperature observations and the Real‐Time Multivariate Madden‐Julian Oscillation (MJO) Index, for the first time, we discussed the daily resolution non‐migrating DE3 temperature tide response to the MJO phenomenon during MJO phases between ±45° latitude from 2003 to 2012 in the Mesosphere and Lower Thermosphere (MLT) region. We found: (a) The DE3 tide significantly depends on different MJO phases in the four seasons above 100 km altitude. The DE3 tidal phase exhibits varying responses to the different MJO phases. (b) The DE3 tide response to the MJO phenomenon is stronger at the solstices than at the equinoxes, and the response at the June solstices is stronger. (c) The symmetric component of the DE3 response to the MJO phenomenon is stronger than the asymmetric component. In summary, the daily resolved DE3 tide response to the MJO phenomenon, especially the DE3 tidal phase dominates certain seasonal characteristics and symmetry in the MLT region.

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.

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.

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.

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.

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 Assessment of MJO Circulation Influence on Air–Sea Interactions for Improved Seasonal Rainfall Predictions over East Africa

AbstractRainfall variability affects agriculture planning and water resource management. In extreme flood and drought events, lives and property are destroyed. This study aims to improve East Africa’s seasonal rainfall prediction by determining the impact of the standard eight Real-time Multivariate Madden–Julian Oscillation (MJO) (RMM) phases on rainfall and using sea surface temperature (SST) response to test the predictability of the March–May (MAM) and October–December (OND) main rainfall seasons over a period of 33 years (1981–2013). Pearson correlation patterns, composite maps, and regression analyses were applied, and the Brier skill score (BSS) and correlation coefficients (CC) were utilized as validation metrics. Low correspondence of rainfall to MJO 1 and MJO 2 was observed except for the months of November and December. Seasonally, MAM and OND correlation patterns with MJO 2 revealed enhanced rainfall over the highlands and insignificant correspondence over coastal areas. Conversely, enhanced MJO 8 corresponded to suppressed rainfall during the June–August season over the coast and the eastern highlands. MAM rainfall was shown to be predictable using Maritime Continent SST indices, with a BSS of 0.41, while OND rainfall was shown to be predictable using Atlantic and Maritime Continent SSTs with a BSS of 0.62. Positive and negative MJO 2 corresponded, respectively, to enhanced and suppressed rainfall during the OND season and was confirmed to be related to, respectively, a positive and negative Indian Ocean dipole (IOD). An IOD year could possibly be triggered by changes in MJO 2 amplitudes observed as early peaks between February and June.

A Cautionary Note on the Long‐term Trend in Activity of the Madden‐Julian Oscillation During the Past Decades

AbstractRecent studies suggest that frequency of active phases of the Madden‐Julian Oscillation (MJO) over the Maritime Continent and western Pacific, that is, the MJO Phases 4–6 defined by the real‐time multivariate MJO (RMM) index, has increased in recent winters. A robust positive trend in MJO Phase 4–6 days during 1979–2015 winters is confirmed in this study. Our analyses, however, suggest that this trend could be exaggerated due to the blended low‐frequency variability signals in the RMM. When the winter RMM is reconstructed using anomalous fields after removing their winter mean instead of the previous 120‐day mean as for the original RMM, the robust trend in MJO Phase 4–6 days can no longer be detected. Therefore, cautions need to be exercised when applying the RMM for studies on the low‐frequency variability and climate trend in MJO activity and using the derived MJO variability to interpret associated changes in climate systems.

Role of the Madden‐Julian Oscillation in the Transport of Smoke From Sumatra to the Malay Peninsula During Severe Non‐El Niño Haze Events

AbstractIn June 2013, the Malay Peninsula experienced severe smoke pollution, with daily surface particulate matter (PM) concentrations in Singapore greater than 350 μg/m3, over 2 times the air quality standard for daily mean PM10 set by the U.S. Environmental Protection Agency. Unlike most haze episodes in the Malay Peninsula in recent decades (e.g., the September 2015 event), the June 2013 haze occurred in the absence of an El Niño, during negative Indian Ocean Dipole conditions, with smoke carried eastward to the Peninsula from fires in the Riau province of central Sumatra. We show that June 2013 was not an exceptional event; inspection of visibility data during 2005–2015 reveals two other severe haze events in the Malay Peninsula (August 2005 and October 2010) occurring under similar conditions. Common to all three events was a combination of anomalously strong westerly winds over Riau province concurrent with late phases of the Real‐Time Multivariate Madden‐Julian Oscillation Index, during negative phases of the Indian Ocean Dipole. Our work suggests that identifying the meteorological mechanism driving these westerly wind anomalies could help stakeholders prepare for future non‐El Niño haze events in Singapore and the Malay Peninsula.

Visualizing and verifying probabilistic forecasts of the Madden‐Julian Oscillation

AbstractWe describe a new approach for presenting probabilistic forecasts of the Madden‐Julian Oscillation (MJO) based on the community standard Real‐time Multivariate MJO (RMM) index, using forecasts from version 2 of the Predictive Ocean Atmosphere Model for Australia. This new display overcomes the difficulty of interpreting a dispersive ensemble plume and directly quantifies the probability for the MJO to occur in each of its eight RMM‐defined phases as well as the weak phase. Beyond monitoring and interpreting predictions of the MJO, this new approach also provides a basis for forecast verification using probability‐based skill scores. Here we present a clear and concise quantitative summary of this innovative method for accessing probability of the state of the MJO in an ensemble forecast. This new method compliments the traditional MJO ensemble forecast display and verification and will benefit global forecasting centers, international MJO working groups, and the World Meteorological Organization Subseasonal to Seasonal Project.

Large‐scale precipitation tracking and the MJO over the Maritime Continent and Indo‐Pacific warm pool

AbstractA large‐scale precipitation tracking (LPT) method is developed to track convection and precipitation associated with the Madden‐Julian oscillation (MJO) using the Tropical Rainfall Measurement Mission 3B42 rainfall data from October to March 1998–2015. LPT uses spatially smoothed 3 day rainfall accumulation to identify and track precipitation features in time with a minimum size of 300,000 km2 and time continuity at least 10 days. While not all LPT systems (LPTs) are attributable to the MJO, among the 199 LPTs, there were 42 with a mean eastward propagation of at least 2 m s−1, which are considered to be MJO convective initiation events. These LPTs capture the diversity of the MJO convection, which is not well depicted by the Real‐time Multivariate MJO (RMM) index or the outgoing longwave radiation MJO index. During the 17 years, there were 17 instances out of 45 with a MJO signature in the RMM without eastward propagating LPTs. Among the 42 eastward propagating LPTs, 24 propagated across the Maritime Continent (MC), which confirms the MC barrier effect. Among the cases that crossed the MC from the Indian Ocean to the western Pacific (MC crossing), 18 (75%) had a significant MJO signature in the RMM index. In contrast, only six (33%) of the non‐MC‐crossing cases occurred with a RMM MJO signal. There is a significant seasonal and interannual variability with MC‐crossing LPTs occurring in December more commonly than other months. More MC‐crossing events were observed during La Niña than El Niño, which is consistent with the observations of stronger and more frequent MJO events identified by RMM during La Niña years.

MJO‐related intraseasonal variation of gravity waves in the Southern Hemisphere tropical stratosphere revealed by high‐resolution AIRS observations

AbstractThe intraseasonal variability of gravity waves (GWs) in the austral summer middle stratosphere was examined using dedicated high‐resolution temperature retrieval from the Atmospheric Infrared Sounder data. Composite maps were made of stratospheric GW temperature variances, large‐scale zonal winds around the tropopause, and precipitation based on the real‐time multivariate Madden‐Julian Oscillation (MJO) index. Regional distributions of these quantities are synchronized with the MJO: The GW variances are larger for stronger precipitation and for more strongly westward wind around the tropopause at a given precipitation. These results suggest that the GWs observed by Atmospheric Infrared Sounder (AIRS) in the stratosphere originate from convection. Moreover, it is shown that the zonal wind around the tropopause likely controls the GW propagation into the stratosphere by a critical level filtering mechanism and/or the GW generation by an obstacle source effect. This means that the MJO can modulate the middle atmospheric circulation by regulating the GWs in two ways, namely, generation and propagation.

Cloud object analysis of CERES Aqua observations of tropical and subtropical cloud regimes: Evolution of cloud object size distributions during the Madden–Julian Oscillation

In this study, we analyze cloud object data from the Aqua satellite between July 2006 and June 2010 that are matched with the real-time multivariate Madden–Julian Oscillation (MJO) index to examine the impact of MJO evolution on the evolutions of the size distributions of cloud object types. These types include deep convective (DC), cirrostratus, shallow cumulus, stratocumulus and overcast-stratus. A cloud object is a contiguous region of the earth with a single dominant cloud-system type. It is found that the cloud object size distributions of some phases depart greatly from the 8-phase combined distribution at large cloud-object diameters. The large-size group of cloud objects contributes to most of the temporal variations during the MJO evolution. For deep convective and cirrostratus cloud objects, there is a monotonic increase in both the number and footprint of large objects from the depressed to mature phases, which is attributed to the development and maturing of deep convection and anvils. The largest increase in the mean diameter during the mature phases that lasts to the early dissipating phase is related to growth of anvil clouds and is accompanied by moderate decreases in small-size objects. For shallow cumulus, the large objects decrease in number at the mature phases, but increase in number for both sizes before the mature phase. The opposite is true for the large overcast-stratus objects. The temporal evolution of large stratocumulus objects is similar to that of deep convective and cirrostratus object types except for peaking slightly earlier.

Evaluating MJO event initiation and decay in the skeleton model using an RMM‐like index

AbstractThe Madden‐Julian oscillation (MJO) skeleton model is a low‐order dynamic model that is capable of simulating many of the observed features of the MJO. This study develops a model‐based “MJO” index that is similar to the well‐known real‐time multivariate MJO (RMM) index to better facilitate comparison between the skeleton model and observational data. Multivariate and univariate empirical orthogonal function (EOF) analyses were performed on the convective heating and zonal wind data taken from the skeleton model for simulations forced with an idealized warm pool and observed sea surface temperatures (SSTs). The leading EOF modes indicated a wave number 1 convectively coupled circulation anomaly with zonal asymmetries that closely resembled the observed RMM EOFs, especially when the model was forced with observed SSTs. The RMM‐like index was used to compute an MJO climatology and document the occurrence of primary, continuing, and terminating MJO events in the skeleton model. The overall amount of MJO activity and event lengths compared reasonably well to observations for such a simple model. Attempts at reconciling the observed geographic distribution of individual MJO initiation and termination events were not successful for the stochastic simulations, though stochasticity is necessary in order to produce composite MJOs that initiate and decay with time scales similar to observations. Finally, analysis indicates that the existence of slow‐moving, eastward traveling waves with higher wave numbers (k ≈ 12) embedded within the large‐scale flow often precedes MJO termination in the skeleton model.

Predicting the Real-Time Multivariate Madden–Julian Oscillation Index through a Low-Order Nonlinear Stochastic Model

Abstract A new low-order nonlinear stochastic model is developed to improve the predictability of the Real-time Multivariate Madden–Julian oscillation (MJO) index (RMM index), which is a combined measure of convection and circulation. A recent data-driven, physics-constrained, low-order stochastic modeling procedure is applied to the RMM index. The result is a four-dimensional nonlinear stochastic model for the two observed RMM variables and two hidden variables involving correlated multiplicative noise defined through energy-conserving nonlinear interaction. The special structure of the low-order model allows efficient data assimilation for the initialization of the hidden variables that facilitates the ensemble prediction algorithm. An information-theoretic framework is applied to the calibration of model parameters over a short training phase of 3 yr. This framework involves generalizations of the anomaly pattern correlation, the RMS error, and the information deficiency in the model forecast. The nonlinear stochastic models show skillful prediction for 30 days on average in these metrics. More importantly, the predictions succeed in capturing the amplitudes of the RMM index and the useful skill of forecasting strong MJO events is around 40 days. Furthermore, information barriers to prediction for linear models imply the necessity of the nonlinear interactions between the observed and hidden variables as well as the multiplicative noise in these low-order stochastic models.

MJO structure associated with the higher-order CEOF modes

The real-time multivariate Madden–Julian oscillation (RMM; MJO) index has been widely employed to monitor the amplitude, phase, and time evolution of MJO events, as the index is formulated from the leading two combined-empirical orthogonal function (CEOF) modes of daily anomalous OLR and 850- and 200-hPa zonal winds, and the modes describe the MJO dynamics well. These two CEOF modes, however, are known to dominate in power spectra at zonal wavenumber one and may underestimate the power and structure at wavenumbers 2–5 where many MJO events are also prominent. This study approximated a baseline for MJO by applying band-pass filters to daily anomalies on 30–100 day periods and at 1–5 eastward propagating waves, as slightly different bands led to the same conclusions. Following the procedures to develop the RMM index, the daily anomalous data were derived and subjected to the CEOF analysis with all modes archived for diagnosis. Different numbers of the leading modes were compared in explained variance, standard deviation (STD), and wavenumber power spectra to describe the overall MJO magnitude and structure, and on the Hovmoller diagrams to represent the evolution of three distinct MJO events. Results show that the two leading CEOF modes explain only a small portion of the power spectra at wavenumbers 2–5. This spectral leakage notably reduces the MJO amplitude, particularly of the OLR in the western Pacific. The CEOF modes 3–10 can withhold power sufficiently such that the anomalies reconstructed by the first 10 modes contribute most of the baseline variance; their structures agree well with the baseline by constituting nearly the same proportion in the region from the central Indian Ocean to the dateline and by providing more complete evolutions of the three MJO events on the Hovmoller diagrams. Meanwhile, these modes introduce a notable amount of power for the equatorial Rossby and Kelvin waves that are partially embedded in the evolution of MJO. The first 50 of the total 432 CEOF modes retain all variance of the baseline MJO, while those higher than 10 contain less information and more noise and can be discarded. Furthermore, this study indicated that the longitudinal STD of the reconstructed anomalies detects the MJO phases and magnitudes in the western Pacific with more physical meaning and in better agreement with the Hovmoller diagrams than the RMM-like amplitude. The results provide an integral figure of the MJO structure from the CEOF analysis and a more robust RMM framework for monitoring the MJO’s evolution in real time and for validating its numerical forecast and simulations.

A Modified Multivariate Madden–Julian Oscillation Index Using Velocity Potential

Abstract A new Madden–Julian oscillation (MJO) index is developed from a combined empirical orthogonal function (EOF) analysis of meridionally averaged 200-hPa velocity potential (VP200), 200-hPa zonal wind (U200), and 850-hPa zonal wind (U850). Like the Wheeler–Hendon Real-time Multivariate MJO (RMM) index, which was developed in the same way except using outgoing longwave radiation (OLR) data instead of VP200, daily data are projected onto the leading pair of EOFs to produce the two-component index. This new index is called the velocity potential MJO (VPM) indices and its properties are quantitatively compared to RMM. Compared to the RMM index, the VPM index detects larger-amplitude MJO-associated signals during boreal summer. This includes a slightly stronger and more coherent modulation of Atlantic tropical cyclones. This result is attributed to the fact that velocity potential preferentially emphasizes the planetary-scale aspects of the divergent circulation, thereby spreading the convectively driven component of the MJO’s signal across the entire globe. VP200 thus deemphasizes the convective signal of the MJO over the Indian Ocean warm pool, where the OLR variability associated with the MJO is concentrated, and enhances the signal over the relatively drier longitudes of the equatorial Pacific and Atlantic. This work provides a useful framework for systematic analysis of the strengths and weaknesses of different MJO indices.

Interaction between the MJO and Polar Circulations

Abstract A tropical–polar connection and its seasonal dependence are examined using the real-time multivariate Madden–Julian oscillation (MJO) (RMM) index and daily indices for the annular modes, the Arctic Oscillation (AO) and the Antarctic Oscillation (AAO). On the intraseasonal time scale, the MJO appears to force the annular modes in both hemispheres. On this scale, during the cold season, the convection in the Indian Ocean precedes the increase of the AO/AAO. Interestingly, during the boreal winter (Southern Hemisphere warm season), strong MJOs in the Indian Ocean are related to a decrease of the AAO index, and AO/AAO tendencies are out of phase. On the longer time scales, a persistent AO/AAO anomaly appears to influence the convection in the tropical belt and impact the distribution of MJO-preferred phases. It is shown that this may be a result of the sea surface temperature (SST) changes related to a persistent AO, with cooling over the Indian Ocean and warming over Indonesia. In the Southern Hemisphere, the SST anomalies are to some extent also related to a persistent AAO pattern, but this relationship is much weaker and appears only during the Southern Hemisphere cold season. On the basis of these results, a mechanism involving the air–sea interaction in the tropics is suggested as a possible link between persistent AO and convective activity in the Indian Ocean and western Pacific.

Climate extremes in Malaysia and the equatorial South China Sea

The southern extent of the South China Sea (SCS) is an important natural resource epicenter for Malaysia which experiences climate extremes. This paper documents the variability of extremes in the equatorial SCS through selected ground-based observations of precipitation in Malaysia and ship-based observations of wind data in the Maritime Continent region, to elucidate the interrelationship between precipitation variability over Malaysia and wind variability over the ocean. The data have been carefully inspected and analyzed, and related to the real-time multivariate Madden–Julian Oscillation (MJO) time series. The analysis suggests that the northeast or boreal winter monsoon dominates extreme rainfall in eastern Malaysian cities. Further, the west coast of Peninsular Malaysia and Borneo Malaysia are affected by the MJO differently than the east coast of Peninsular Malaysia. From the wind analysis we found that average zonal wind is westerly from May to September and easterly from November to April. When the active (convective) phase of the MJO is centered over the Maritime Continent, the strong westerly wind bursts are more frequent in the South China Sea. While more investigation is needed, these results suggest that the status of the Madden–Julian Oscillation can be used to help forecast climate extremes in areas of Malaysia.