Propagation Of Madden-Julian Oscillation Research Articles

Indonesian Throughflow promoted eastward propagation of the Madden-Julian Oscillation

Understanding the impacts of the Indonesian Throughflow (ITF) on the eastward propagation of the Madden-Julian Oscillation (MJO) is crucial for accurately simulating the MJO and achieving high-skill sub-seasonal predictions. Our analyses demonstrate a significant enhancement of MJO eastward propagation due to the strong ITF. Blocking the ITF decreases the eastward sea surface temperature (SST) gradient over the tropical Indian Ocean, hindering MJO propagation across the Maritime Continent (MC). Removing the MJO circulation-induced intraseasonal variability of the ITF transport also weakens the eastward propagation of the MJO, as the MJO easterly winds enhance the ITF transport and warm the eastern tropical Indian Ocean. These experiments reveal that mean and intraseasonal variability of the ITF transport contribute to 73% and 42% of the eastward propagation of the MJO over the MC, respectively. The findings presented in this study highlight the significant role of the ITF in shaping the propagation of the MJO.

MJO Diversity in CMIP6 Models

Abstract Recent studies have shown that individual Madden–Julian oscillation (MJO) events can be categorized into four types based on their propagation characteristics: standing, jumping, slow-propagating, and fast-propagating MJOs. While their structures and impacts are well documented in observations, their representation in state-of-the-art climate models has not been investigated. This study evaluates the four types of MJOs in phase 6 of Coupled Model Intercomparison Project (CMIP6) models. While most models show reasonable MJO propagation characteristics, their performance varies among MJO types, with better performance for the propagating MJO types. To identify the factors that drive each MJO type, background conditions at the surface, troposphere, and stratosphere are examined. We found that the standing and fast MJOs are closely associated with sea surface temperature (SST) and precipitable water (PW) distributions. Specifically, negative and positive SST and PW anomalies are observed over the equatorial Pacific during the standing and fast-propagating MJOs, respectively. In contrast, the jumping and slow-propagating MJOs do not show noticeable SST and PW distributions, suggesting that they may be more strongly influenced by the internal dynamics than by the background conditions. It is further found that the models with more frequent standing MJO than fast MJO generally have stronger negative biases in both SST and PW over the equatorial western Pacific. Although the standing MJO is also preferred when the stratospheric wind at 50 hPa is westerly, such a relationship is absent in the models. These results suggest that MJO diversity in climate models could be improved by better simulation of the mean state, especially for the standing and fast-propagating MJOs.

Two‐way feedback between the Madden–Julian Oscillation and diurnal warm layers in a coupled ocean–atmosphere model

AbstractDiurnal warm layers develop in the upper ocean on sunny days with low surface wind speeds. They rectify intraseasonal sea‐surface temperatures (SSTs), potentially impacting intraseasonal weather patterns such as the Madden–Julian Oscillation (MJO). Here we analyse 15‐lead‐day forecast composites of coupled ocean–atmosphere and atmosphere‐only numerical weather prediction (NWP) models of the UK Met Office to reveal that the presence of diurnal warming of SST (dSST) leads to a faster MJO propagation in the coupled model compared with the atmosphere‐only model. To test the feedback between the MJO and the dSST, we designed a set of experiments with instantaneous vertical mixing over the top 5 or of the ocean component of the coupled model. Weaker dSST in the mixing experiments leads to a slower MJO over 15 lead days. The dSST produces a increase in the MJO phase speed between the coupled and the atmosphere‐only model. An additional increase is found for other coupling effects, unrelated to the dSST. A two‐way feedback manifests in the coupled model over the 15 lead days of the forecast between the MJO and the dSST. The MJO regime dictates the strength of the dSST and the dSST rectifies the intraseasonal anomalies of SST in the coupled model. Stronger dSST in the coupled model leads to stronger intraseasonal anomalies of SST. The MJO convection responds to these SSTs on a seven‐lead‐day timescale, and feeds back into the SST anomalies within the next three lead days. Overall, this study demonstrates the importance of high vertical resolution in the upper ocean for predicting the eastward propagation of the MJO in an NWP setting, which is potentially impactful for seasonal predictions and climate projections, should this feedback be unrepresented in the models.

Effects of Surface Turbulence Flux Parameterizations on the MJO: The Role of Ocean Surface Waves

Abstract This study investigates the sensitivity of the Madden–Julian oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air–sea coupling using a fully coupled ocean–atmosphere–wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed–dependent bulk algorithms (NCAR and COARE3.0a) and one experiment with wave-state-dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection–circulation coupling than NCAR, it exhibits anomalous MJO convection east of the date line. The wave-state-dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the date line. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the date line. These findings highlight the role of surface fluxes in MJO simulation fidelity. Most importantly, we show that the proper treatment of wave-induced effects in bulk flux parameterization improves the simulation of coupled climate variability.

Assessment of the Madden‐Julian Oscillation in CMIP6 Models Based on Moisture Mode Theory

AbstractThe moist processes of the Madden‐Julian Oscillation (MJO) in the Coupled Model Intercomparison Project Phase 6 models are assessed using moisture mode theory‐based diagnostics over the Indian Ocean (10°S–10°N, 75°E–100°E). Results show that no model can capture all the moisture mode properties relative to the reanalysis. Most models satisfy weak temperature gradient balance but have unrealistically fast MJO propagation and a lower moisture‐precipitation correlation. Models that satisfy the most moisture mode criteria reliably simulate a stronger MJO. The background moist static energy (MSE) and low‐level zonal winds are more realistic in the models that satisfy the most criteria. The MSE budget associated with the MJO is also well‐represented in the good models. Capturing the MJO's moisture mode properties over the Indian Ocean is associated with a more realistic representation of the MJO and thus can be employed to diagnose MJO performance.

MJO Structure–Propagation Nexus and Impacts of Background Mean States in CMIP6 Models

Abstract Eastward propagation is an essential feature of the Madden–Julian oscillation (MJO). Yet, it remains a challenge to realistically simulate it by global climate system models, and the reasons are not fully understood. This study evaluates the capability of 20 Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating MJO’s eastward propagation and its intrinsic links with the dynamic–thermodynamic structures and the background mean states, aiming at better understanding the sources of the simulation errors. The metrics to evaluate the MJO internal dynamics consists of six parameters: 1) the east–west asymmetry in the low-level circulation, 2) the boundary layer moisture convergence propagation, 3) the vertical tilt of equivalent potential temperature or moist static energy, the vertical structures of 4) diabatic heating and 5) available potential energy generation, and 6) upper-level diabatic heating and divergence. We also gauge the performance of three MJO-related background mean-state fields, including precipitation, sea surface temperature, and low-level moist static energy. It is argued that these parameters are relevant internal and external factors that could affect MJO eastward propagation. We find that the boundary layer moisture convergence is most tightly coupled with the eastward propagation of MJO and controls the premoistening, destabilization, and the leading low-level diabatic heating and available potential energy generation. The CMIP6 models exhibit significant improvements against CMIP5 models in simulating MJO dynamic–thermodynamic structures and the mean states. The diagnostics in this study could help to identify the possible processes related to CMIP6 models’ shortcomings and shed light on how to improve simulation of MJO eastward propagation in the future.

Impact of MJO Propagation Speed on Active Atlantic Tropical Cyclone Activity Periods

AbstractThe Madden‐Julian Oscillation (MJO) is often used for subseasonal forecasting of tropical cyclone (TC) activity. However, TC activity still has considerable variability even given the state of the MJO. This study evaluates the connection between MJO propagation speed with Atlantic TC activity and possible physical mechanisms guiding this relation. We find the Atlantic sees the highest accumulated cyclone energy (ACE) during MJO phase 2. However, the odds of above average ACE in the Atlantic is greatest during slow MJO propagation. We find that slow propagation of the MJO results in lower vertical wind shear anomalies over the Caribbean and main development region compared with typical MJO propagation. Typical MJO propagation produces an amplified height pattern and lower height anomalies along the region of the tropical upper tropospheric trough which is known to impede Atlantic TC activity. Slow MJO propagation sees weaker height anomalies over the Atlantic.

Propagation Characteristics of Madden Julian Oscillation in the Indonesian Maritime Continent: Case Studies for 2020-2022

Madden-Julian Oscillation (MJO) can affect weather and climate variability in the Indonesian Maritime Continent. MJO propagation is not always the same, previous research has classified MJO into 4 categories: slow, fast, stand, and jump. The objective of this study is to investigate the differences in MJO propagation and the factors that impact it. Daily data for variables such as Outgoing Longwave Radiation (OLR), zonal wind, and sea surface temperature are utilized in this research. The collected data is processed using composite methods based on the 8 MJO phases, with a specific focus on the years 2020, 2021, and 2022. The research findings suggest that warm sea surface temperatures in the Pacific Ocean and zonal winds dominated by Kelvin waves are favorable for MJO propagation. Conversely, cooling sea surface temperatures in the Pacific Ocean and zonal winds dominated by equatorial Rossby waves can hinder MJO propagation. Future researchers are expected to examine the impact of MJO propagation during extreme rainfall occurrences in several regions of Indonesia, as well as the application of machine learning and deep learning methods to predict MJO propagation in the future.

The effect of diurnal warming of sea‐surface temperatures on the propagation speed of the Madden–Julian oscillation

AbstractThe diurnal warm layer in the upper ocean develops during low surface winds and high incoming solar radiation conditions, often increasing sea‐surface temperatures (SSTs) by up to 1°C. The suppressed phase of the Madden–Julian Oscillation (MJO) favours the formation of such a layer. Here, we analyse the coupled ocean–atmosphere and atmosphere‐only numerical weather prediction systems of the UK Met Office to reveal that important differences arise from the representation of the diurnal warm layer in the coupled model. Though both models are skilful in predicting the MJO to at least a 7‐day lead time, the coupled model predicts approximately 12% faster MJO RMM phase speed propagation than the atmosphere‐only model due to the ability to resolve diurnal warming in the upper ocean that rectifies onto MJO‐associated SST anomalies. The diurnal warming of SST (dSST) in the coupled model leads to an increase in daily mean SST compared with the atmosphere‐only model persisted foundation SST. The strength of the dSST in the coupled model is modulated by MJO conditions. During suppressed MJO conditions on lead day 1, the dSST is enhanced, leading to 0.2°C warmer daily mean MJO‐associated SST anomalies and increased convection in the coupled model by lead day 7. During active MJO convection, the dSST is suppressed, leading to 0.1°C colder MJO‐associated SST anomalies in the coupled model and reduced convection by lead day 7. This variability in dSST further amplifies the MJO propagation speed, underlining the importance of the two‐way feedback between the MJO and the diurnal cycle of SST and the need to accurately represent this process in coupled models.

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.

ENSO Modulation of Global MJO and Its Impacts on South America

Abstract Changes in the Madden–Julian oscillation (MJO) and its impacts on the South American monsoon season during different El Niño–Southern Oscillation (ENSO) states [El Niño (EN), La Niña (LN), neutral (NT)] are analyzed in the global context of the MJO-propagating anomalies of convection and circulation. The background ENSO-related changes influence several aspects of MJO (relative occurrence of phases, propagation, convection, and teleconnections), and therefore modify the MJO impacts on South America (SA), such as precipitation anomalies and frequency of extreme events, as well as their distribution throughout the MJO cycle. Among the changes are the following: 1) a delay in the teleconnection between the central-east Pacific and SA, from MJO phase 8 in LN (MJOLNphase8) to MJO phase1 in EN (MJOENphase1); 2) enhanced MJO convection in the central-east subtropical South Pacific in MJOLNphases7 + 8 and a little farther east in MJOENphases8 + 1, in a region efficient in generating teleconnections that produce rainfall anomalies over central-east SA (CESA), especially the South Atlantic convergence zone (SACZ), strongest one phase earlier in LN (MJOLNphase8) than in EN (MJOENphase1), and a little shifted east in the latter than in the former; 3) enhancement of the extratropical teleconnection and its impacts over the SACZ in both EN and LN (with regard to NT), indicating nonlinear effects on MJO impacts over SA; 4) predominant increase (or reduction) in the frequency of extreme events over SA regions where both ENSO and MJO contribute in the same direction, with the greatest increase over CESA during EN in MJOENphase1 and over Southeast SA (SESA) in MJOENphase3. Significance Statement The changes produced by different El Niño–Southern Oscillation background states (neutral, El Niño, La Niña) in the Madden–Julian oscillation (MJO) and its impacts on precipitation over South America (SA) are disclosed for the austral summer monsoon season, when MJO is strongest. The reliability of the results is enhanced by using observed rainfall data. The background states affect MJO propagation, circulation, and convection, producing significant differences in precipitation and extremes over densely populated regions, besides phase shifts of the strongest impacts. The results are relevant to subseasonal prediction, since MJO is a key predictability source, to validate models and describe realistically the impacts over SA in each MJO phase. Models’ skill in simulating these results is assessed in a follow-up work.

Systematic Occurrence Cycle of Typical RH‐Profiles During the MJO: Evidence for Ubiquitous Pre‐Moistening

AbstractWe describe how typical relative humidity (RH) profiles change systematically through the phases of the Madden–Julian Oscillation (MJO). We use 18 years of classified RH‐profiles from the Atmospheric Infrared Sounder, clustered without prior knowledge of large‐scale dynamics or occurrence‐region. Occurrence probability (OP) anomalies of RH‐profiles classes exhibit classical MJO patterns: Large positive OP anomalies of the RH‐profile class with most moisture in the free troposphere are co‐located with the largest positive precipitation anomalies. About 10 days prior to this deep convective core large OP anomalies of a RH‐profile class occur consistent with lower atmospheric moistening, supporting a ubiquitous role of pre‐moistening in MJO propagation. Since each RH‐profile class is associated with distinct dynamics (most of which are subgrid‐scale to climate models) our results can serve as process‐based diagnostics to investigate parameterization shortcomings of climate models preventing them to simulate the MJO accurately.

The Idealized Aquaplanet Maritime Continent Barrier Effect on the MJO Predictability

Abstract Studies have indicated exaggerated Maritime Continent (MC) barrier effect in simulations of the Madden–Julian oscillation (MJO), a dominant source of subseasonal predictability in the tropics. This issue has plagued the modeling and operational forecasting communities for decades, while the sensitivity of MC barrier on MJO predictability has not been addressed quantitatively. In this study, perfect-model ensemble forecasts are conducted with an aquaplanet configuration of the Community Earth System Model version 2 (CESM2) in which both basic state and tropical modes of variability are reasonably simulated with a warm pool–like SST distribution. When water-covered terrain mimicking MC landmasses is added to the warm pool–like SST framework, the eastward propagation of the MJO is disturbed by the prescribed MC aqua-mountain. The MJO predictability estimate with the perfect-model experiment is about 6 weeks but reduces to about 4 weeks when the MJO is impeded by the MC aqua-mountain. Given that the recent operational forecasts show an average of 3–4 weeks of MJO prediction skill, we can conclude that improving the MJO propagation crossing the MC could improve the MJO skill to 5–6 weeks, close to the potential predictability found in this study (6 weeks). Therefore, more effort toward understanding and improving the MJO propagation is needed to enhance the MJO and MJO-related forecasts to improve the subseasonal-to-seasonal prediction.

East African Monsoon as a Drawbridge for the Circumnavigation of Madden–Julian Oscillation Events

AbstractThe seasonality of circumnavigation of Madden–Julian Oscillation (MJO) events is examined using 42 years of observations, reanalysis, and global model simulations. MJO events are most likely to propagate across the Atlantic Ocean, Africa and back to the equatorial Indian Ocean relatively unweakened during March–April–May and to a lesser extent during September–October–November. During these seasons, referred to as the “long‐rain” and “short‐rain” periods of East African Monsoon (EAM), precipitation is near the equator and extends farthest east toward the Indian Ocean. Moisture budget analysis of a circumnavigating MJO event under real and hypothetical seasonally varying background conditions indicates that the seasonal zonal movement of the zonal component of the background circulation regulates the moistening of MJO crossing from Eastern Africa to the Indian Ocean. Ensembles of Energy Exascale Earth System Model simulations of the MJO event under idealized seasonally varying background state confirm the observed drawbridge‐like role of the EAM in the propagation of MJO.

Response of the Madden–Julian Oscillation and Tropical Atmosphere to Changes in Oceanic Mixed Layer Depth over the Indian Ocean

Abstract The Madden–Julian oscillation (MJO) is a component of tropical variability that influences high-impact events such as hurricane activity and Asian monsoons on intraseasonal (2–8 weeks) time scales. However, the atmosphere–ocean dynamics responsible for the MJO are highly debated. To gain insight into MJO–Indian Ocean dynamics, we conduct climate model experiments where the ocean is replaced by a motionless slab whose thickness, called the mixed layer depth (MLD), varies in space but not in time. Changes in the MLD and ocean heat convergence over the Indian Ocean have no discernible impact on MJO propagation, predictability, or variability within the Community Earth System Model (CESM) version 1.2.1. This suggests that ocean dynamics may not be critical to the MJO over the Indian Ocean in this dynamical model (CAM5 coupled to motionless slab). To diagnose changes in intraseasonal variability beyond the MJO, a discriminant analysis technique is used to optimize differences in variability between experiments. This analysis reveals that differences caused by changing Indian Ocean MLD were restricted mostly to local surface fluxes and could be explained by simple energy balance physics. Despite modeling adjustments intended to preserve the climate, the control slab has a warmer climate than the fully coupled model. The resulting changes in the mean climate are consistent with changes theoretically expected from global warming, particularly the “wet-gets-wetter” mechanism. Significance Statement The Madden–Julian oscillation (MJO) is a tropical eastward-moving pulse of convection that can influence a wide variety of global phenomena. Currently, models do not capture many key aspects of the MJO such as speed and spatial structure. The uppermost ocean layer that communicates with the atmosphere is widely believed to play a large role in the evolution of the MJO. To test the importance of ocean dynamics on simulated MJO, a slab-model configuration is used to allow the atmosphere and ocean to communicate through surface fluxes of heat and moisture while suppressing interactive ocean currents. Changes to the upper ocean did not impact the MJO in our model setup.

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.

Land‐Locked Convection as a Barrier to MJO Propagation Across the Maritime Continent

AbstractLarge‐scale convection associated with the Madden‐Julian Oscillation (MJO) initiates over the Indian Ocean and propagates eastward across the Maritime Continent (MC). Over the MC, MJO events are generally weakened due to complex interactions between the large‐scale MJO and the MC landmass. The MC barrier effect is responsible for the dissipation of 40%–50% of observed MJO events and is often exaggerated in weather and climate models. We examine how MJO propagation over the MC is affected by two aspects of the MC—its land‐sea contrast and its terrain. To isolate the effects of mountains and land‐sea contrast on MJO propagation, we conduct three high‐resolution coupled atmosphere‐ocean model experiments: (a) control simulation (CTRL) of the 2011 November–December MJO event, (b) flattened terrain without MC mountains (FLAT), and (c) no‐land simulation (WATER) in which the MC islands are replaced with 50 m deep ocean. CTRL captures the general properties of the diurnal cycle of precipitation and MJO propagation across the MC. The WATER simulation produces a more intense and smoother‐propagating MJO compared with that of CTRL. In contrast, the convergence of sea breezes in the FLAT simulation produces much more organized convection and precipitation far inland than in CTRL, which results in a stronger barrier effect to MJO propagation. The land‐sea contrast induced land‐locked convection weakens the MJO's convective organization. The land‐locked convective systems over land in FLAT are more intense, grow larger, and last longer, which is more detrimental to MJO propagation over the MC, than the mountains that are present in CTRL.

The Role of Surface Fluxes in MJO Propagation through the Maritime Continent

Abstract The “barrier effect” of the Maritime Continent (MC) is a known hurdle in understanding the propagation of the Madden–Julian oscillation (MJO). To understand the differing dynamics of MJO events that propagate versus stall over the MC, a new tracking algorithm utilizing 30–96-day-filtered NOAA Interpolated OLR anomalies is presented. Using this algorithm, MJO events can be identified, tracked, and described in terms of their propagation characteristics. Latent heat flux from OAFlux and CYGNSS surface winds and fluxes are compared for MJO events that do and do not propagate through the MC. Events that successfully propagate through the MC demonstrate regional surface flux anomalies that are stronger, more spatially coherent, and have a larger fetch. The spatial scale of convective anomalies for events that successfully propagate through the MC region is also larger than for terminating events. Large-scale enhancement of latent heat fluxes near and to the east of the date line, equally driven by dynamic and thermodynamic effects, also accompanies MJO events that successfully propagate through the MC. These findings are placed in the context of recent theoretical models of the MJO in which latent heat fluxes are important for propagation and destabilization.

Comparison of Madden-Julian oscillation in three super El Niño events

This paper investigated the characteristics of Madden-Julian Oscillation (MJO) in three super El Niño events (i.e., 1982/83, 1997/98 and 2015/16 El Niño events) based on reanalysis data. MJO with apparent eastward propagation can be observed during the developing stages of these three super El Niño events. Enhanced MJO zonal wind was observed over the western Pacific, especially in 1997/98 and 2015/16 El Niño events, which is mainly attributed to the effects of tropical background circulation and extratropical anomalous circulation. During the mature stages of 1982/83 and 1997/98 El Niño events, MJO with noticeable eastward propagation cannot be observed, and the MJO zonal wind amplitude at 850 hPa was weakened (enhanced) over the Indian Ocean and western Pacific (central and eastern Pacific). However, MJO zonal wind amplitude over the central and eastern Pacific was enhanced and the prominent eastward propagation was also found in the mature stage of 2015/16 El Niño. The eastward propagation of MJO was also observed during the decaying stages of the three super El Niño events, but its intensity was weaker compared with the developing and mature stages. The abnormal activity of MJO during the mature and decaying stages may be closely related to the characteristics in circulation and moisture anomalies caused by El Niño and the seasonal cycle of circulation and moisture. In addition, this study found that the RMM index and MJO zonal wind amplitude may lead to contradictory results in identifying the characteristics of MJO activity, especially during the developing and decaying stages.

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.