Simulated Madden–Julian Oscillation Research Articles

Assessment of upper-ocean variability and the Madden-Julian Oscillation in extended-range air-ocean coupled mesoscale simulations

Atmosphere-ocean interaction, particular the ocean response to strong atmospheric forcing, is a fundamental component of the Madden-Julian Oscillation (MJO). In this paper, we examine how model errors in previous Madden-Julian Oscillation (MJO) events can affect the simulation of subsequent MJO events due to increased errors that develop in the upper-ocean before the MJO initiation stage. Two fully coupled numerical simulations with 45-km and 27-km horizontal resolutions were integrated for a two-month period from November to December 2011 using the Navy’s limited area Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). There are three MJO events that occurred subsequently in early November, mid-November, and mid-December during the simulations. The 45-km simulation shows an excessive warming of the SSTs during the suppressed phase that occurs before the initiation of the second MJO event due to erroneously strong surface net heat fluxes. The simulated second MJO event stalls over the Maritime Continent which prevents the recovery of the deep mixed layer and associated barrier layer. Cross-wavelet analysis of solar radiation and SSTs reveals that the diurnal warming is absent during the second suppressed phase after the second MJO event. The mixed layer heat budget indicates that the cooling is primarily caused by horizontal advection associated with the stalling of the second MJO event and the cool SSTs fail to initiate the third MJO event. When the horizontal resolution is increased to 27-km, three MJOs are simulated and compare well with observations on multi-month timescales. The higher-resolution simulation of the second MJO event and more-realistic upper-ocean response promote the onset of the third MJO event. Simulations performed with analyzed SSTs indicate that the stalling of the second MJO in the 45-km run is a robust feature, regardless of ocean forcing, while the diurnal cycle analysis indicates that both 45-km and 27-km ocean resolutions respond realistically when provided with realistic atmospheric forcing. Thus, the problem in the 45-km simulation appears to originate in the atmosphere. Additional simulations show that while the details of the simulations are sensitive to small changes in the initial integration time, the large differences between the 45-km and 27-km runs during the suppressed phase in early December are robust.

MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJO amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.

Identifying a key physical factor sensitive to the performance of Madden–Julian oscillation simulation in climate models

A key physical factor in regulating the performance of Madden–Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization’s Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

Roles of deep and shallow convection and microphysics in the MJO simulated by the Model for Prediction Across Scales

AbstractThe November event of the Madden‐Julian oscillation (MJO) during the Dynamics of North Atlantic Models (DYNAMO) field campaign was simulated using the global compressible nonhydrostatic Model for Prediction Across Scales with global coarse (60 and 15 km) and regional (the Indian Ocean) cloud‐permitting (3 km) meshes. The purpose of this study is to compare roles of parameterized deep and shallow cumulus and microphysics in MJO simulations. Two cumulus schemes were used: Tiedtke and Grell‐Freitas. The deep and shallow components of Tiedtke scheme can be turned on and off individually. The results reveal that microphysics alone (without cumulus parameterization) is able to produce strong signals of the MJO in precipitation with 3 km mesh and weak MJO signals with 15 km mesh. A shallow scheme (Tiedtke) along with microphysics strengthens the MJO signals but makes them less well organized on large scales. A deep cumulus scheme can either improve the large‐scale organization of MJO precipitation produced by microphysics and shallow convection (Tiedtke) or impair them (Grell‐Freitas). The deep scheme of Tiedtke cannot reproduce the MJO well without its shallow counterpart. The main role of shallow convection in the model is to transport moisture upward to the lower to middle troposphere. By doing so, it removes dry biases in the lower to middle troposphere, a distinct feature in simulations with weak or no MJO signals, and enhances total precipitation and diabatic heating produced by microphysics and deep cumulus schemes. Changing model grid spacing from 60 to 15 km makes a little difference in the model fidelity of reproducing the MJO. All roles of shallow convection in 15 km simulations with parameterized deep convection cannot be reproduced in 3 km simulations without parameterized deep convection. Results from this study suggest that we should pay more attention to the treatment of shallow convection and its connection to other parameterized processes for improving MJO simulations. In other words, a holistic approach should be taken that consider parameterization of shallow cumulus, microphysics, boundary layer, and deep cumulus as a whole for model improvement.

MJO simulation in a cloud‐system‐resolving global ocean‐atmosphere coupled model

AbstractAn observed Madden‐Julian Oscillation (MJO) propagating from the central Indian Ocean to the western Pacific from 15 December 2006 to 10 January 2007 was successfully simulated by a cloud‐system‐resolving global ocean‐atmosphere coupled model without parameterization of cumulus convection. We found that the ocean coupling has significant impacts on the MJO simulation, e.g., strength of the moisture convergence, and the timing and strength of the westerly wind burst over the Maritime Continent. The model also generally well simulated the decay of the MJO in the western Pacific, as well as the changes in sea surface temperature. These results demonstrate that the cloud‐system‐resolving global ocean‐atmosphere coupled model can be used for realistic MJO simulation.

Response of the Superparameterized Madden–Julian Oscillation to Extreme Climate and Basic-State Variation Challenges a Moisture Mode View

Abstract The climate sensitivity of the Madden–Julian oscillation (MJO) is measured across a broad range of temperatures (1°–35°C) using a convection-permitting global climate model with homogenous sea surface temperatures. An MJO-like signal is found to be resilient in all simulations. These results are used to investigate two ideas related to the modern “moisture mode” view of MJO dynamics. The first hypothesis is that the MJO has dynamics analogous to a form of radiative convective self-aggregation in which longwave energy maintenance mechanisms shut down for SST ≪ 25°C. Inconsistent with this hypothesis, the explicitly simulated MJO survives cooling and retains leading moist static energy (MSE) budget terms associated with longwave destabilization even at SST < 10°C. Thus, if the MJO is a form of longwave-assisted self-aggregation, it is not one that is temperature critical, as is observed in some cases of radiative–convective equilibrium (RCE) self-aggregation. The second hypothesis is that the MJO is propagated by horizontal advection of column MSE. Inconsistent with this view, the simulated MJO survives reversal of meridional moisture gradients in the basic state and a striking role for horizontal MSE advection in its propagation energy budget cannot be detected. Rather, its eastward motion is balanced by vertical MSE advection reminiscent of gravity or Kelvin wave dynamics. These findings could suggest a tight relation between the MJO and classic equatorial waves, which would tend to challenge moisture mode views of MJO dynamics that assume horizontal moisture advection as the MJO’s propagator. The simulation suite provides new opportunities for testing predictions from MJO theory across a broad climate regime.

Effects of moisture feedback in a frictional coupled Kelvin–Rossby wave model and implication in the Madden–Julian oscillation dynamics

The authors extend the original frictional wave dynamics and implement the moisture feedback (MF) to explore the effects of planetary boundary layer (PBL) process and the MF on the Madden–Julian Oscillation (MJO). This new system develops the original frictional wave dynamics by including the moisture tendency term (or the MF mode), along with a parameterized precipitation based on the Betts–Miller scheme. The linear instability analysis of this model provides solutions to elucidate the behaviors of the “pure” frictional convergence (FC) mode and the “pure” MF mode, respectively, as well as the behaviors of the combined FC–MF mode or the dynamical moisture mode. These results show that without the PBL frictional moisture convergence, the MF mode is nearly stationary and damped. Not only does the PBL frictional feedback make the damping MF mode grow with preferred planetary scale but it also enables the nearly stationary MF mode to move eastward slowly, resulting in an oscillation with a period of 30–90 days. This finding suggests the important role of the frictional feedback in generating eastward propagating unstable modes and selecting the preferred planetary scales. The MF process slows down the eastward-propagating short-wave FC mode by delaying the occurrence of deep convection and by enhancing the Rossby wave component. However, the longest wave (wavenumber one) is insensitive to the MF or the convective adjustment time, indicating that the unstable longest wave is primarily controlled by PBL frictional feedback process. Implications of these theoretical results in MJO simulation in general circulation models are discussed.

Assessment of Madden–Julian oscillation simulations with various configurations of CESM

This paper presents an assessment of the Madden–Julian oscillation (MJO) simulated in five experiments using the Community Earth System Model under different model settings. The analysis focused on the effects of air–sea coupling, resolution and atmospheric physics on the basic characteristics of the MJO, including intraseasonal variance, wavenumber-frequency characteristics and eastward propagation, using outgoing longwave radiation (OLR), zonal winds at 850 hPa (U850) and at 200 hPa (U200). Five experiments are conducted for this purpose including one atmospheric model—Community Atmosphere model version 4 (CAM4), two coupled models with CAM4 or Community Atmosphere model version 5 (CAM5) as the atmospheric component at a low resolution (CLP4_2d, CPL5_2d) and two the same coupled model with a high resolution (CPL4_1d and CLP5_1d). The results show that all models have better intraseasonal characteristics in U850 than in OLR. The uncoupled model CAM4 has lower fidelity than the coupled models in characterizing MJO basic features including the temporal and spatial intraseasonal variability and the eastward propagation. With ocean feedback, the coherence of convection and circulation is improved in the coupled models. The higher resolution is helpful in improving ISV spatial distribution and eliminating low frequency bias in the frequency-wavenumber spectra although it has little improvement to MJO-band variance (power) in frequency-wavenumber spectra. The new shallow convection scheme in CAM5 improves the moisture process of the lower troposphere so that CPL5_2d and CPL5_1d have more realistic eastward propagation speed in the boreal winter and better northward propagation in the boreal summer than other models. However, the strength of the convective MJO signal in CPL5_2d and CPL5_1d are weaker than other models and observations, which is probably one of the most spurious features in CPL5_2d and CPL5_1d experiments, suggesting that the CAM5 has a weaker convection activity than its predecessor.

Role of Longwave Cloud–Radiation Feedback in the Simulation of the Madden–Julian Oscillation

Abstract The role of the cloud–radiation interaction in the simulation of the Madden–Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (<5 mm day−1). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (<5 mm day−1). Models with a greater GEF in the strong precipitation anomaly regime (>30 mm day−1) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud–radiation interaction is a crucial process for climate models to correctly represent the MJO.

Constraints on Cumulus Parameterization from Simulations of Observed MJO Events

Abstract Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

What is the Role of the Sea Surface Temperature Uncertainty in the Prediction of Tropical Convection Associated with the MJO?

Abstract This study investigated the influence of the uncertainty in the sea surface temperature (SST) on the representation of the intraseasonal rainfall variability associated with the Madden–Julian oscillation (MJO) and how this influence varies with convection parameterization. The study was motivated by the fact that there exist substantial differences in observational SST analyses, and by the possibility that lacking sufficient accuracy for SSTs in dynamical models may degrade the MJO simulation and prediction. Experiments for the DYNAMO intensive observing period were carried out using the NCEP atmospheric Global Forecast System (GFS) with three convection schemes forced by three SST specifications. The SST specifications included the widely used National Climatic Data Center (NCDC) daily SST analysis, the TRMM Microwave Imager (TMI) SST retrieval, and an SST climatology that only contains climatological seasonal cycle. The experiments show that for all convection schemes, the advantage of using observed (TMI and NCDC) SSTs over the climatology SSTs can be seen as early as 5 days to 1 week after the start of the forecast. Further, the prediction with TMI SSTs was more skillful than that with the NCDC SSTs, indicating that the current level of SST uncertainties in the observational analyses can lead to large differences when they are used as the lower boundary conditions. The results suggest that the simulation and prediction can be improved with an atmosphere-only model forced by more accurate SSTs, or with a coupled atmosphere–ocean model that has a more realistic representation of the SST variability. Differences in the prediction among the convection schemes are also presented and discussed.

Vertical structure and physical processes of the Madden‐Julian oscillation: Exploring key model physics in climate simulations

AbstractAimed at reducing deficiencies in representing the Madden‐Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process‐oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large‐scale rainfall partition and low‐level mean zonal winds over the Indo‐Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low‐level relative humidity difference between high‐ and low‐rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud‐radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air‐sea interaction can lead to significant improvement in simulating the MJO.

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

Abstract A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model’s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model’s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

The parametric sensitivity of CAM5's MJO

AbstractWe systematically explore the ability of the Community Atmospheric Model version 5 (CAM5) to simulate the Madden‐Julian Oscillation (MJO), through an analysis of MJO metrics calculated from a 1100‐member perturbed parameter ensemble of 5 year simulations with observed sea surface temperatures. Parameters from the deep convection scheme make the greatest contribution to the variance in MJO simulation quality with a much smaller contribution from parameters in the large‐scale cloud, shallow convection, and boundary layer turbulence schemes. Improved MJO variability results from a larger lateral entrainment rate and a reduction in the precipitation efficiency of deep convection that was achieved by a smaller autoconversion of cloud to rainwater and a larger evaporation of convective precipitation. Unfortunately, simulations with an improved MJO also have a significant negative impact on the climatological values of low‐level cloud and absorbed shortwave radiation, suggesting that structural in addition to parametric modifications to CAM5's parameterization suite are needed in order to simultaneously well simulate the MJO and mean‐state climate.

A Unified Convection Scheme (UNICON). Part II: Simulation

Abstract A unified convection scheme (UNICON) is implemented into the Community Atmosphere Model, version 5 (CAM5), and tested in single-column and global simulations forced by observed sea surface temperature. Compared to CAM5, UNICON substantially improves the single-column simulations of stratocumulus-to-cumulus transition and shallow and deep convection cases. The global performance of UNICON is similar to CAM5 with a relative spatiotemporal root-mean-square error (RMSE) of 0.777 (0.755 in CAM5) against the earlier version of the model (CCSM3.5). The notable improvements in the UNICON-simulated climatologies over CAM5 are seasonal precipitation patterns (i.e., monsoon) over the western Pacific and South Asia, reduced biases of cloud radiative forcing in the tropical deep convection regions, aerosol optical depth in the tropical and subtropical regions, and cumulus fraction and in-cumulus condensate. One notable degradation is that UNICON simulates warmer near-surface air temperature over the United States during summer. In addition to the climatology, UNICON significantly improves the simulation of the diurnal cycle of precipitation and the Madden–Julian oscillation (MJO). The surface precipitation simulated by UNICON is a maximum in the late afternoon (early afternoon in CAM5) over the summer continents and in the early morning (predawn in CAM5) over the ocean with a fairly realistic amplitude of the diurnal cycle. Sensitivity simulations indicate that the key for successful MJO simulation in UNICON is a seamless parameterization of the updraft plume dilution rate as convection evolves from shallow to deep convection. The mesoscale perturbation of the vertical velocity and the thermodynamic scalars of convective updrafts is an additional requirement for simulating the observed diurnal cycle of precipitation.

Resolving the upper-ocean warm layer improves the simulation of the Madden–Julian oscillation

Here we show that coupling a high-resolution one-column ocean model to an atmospheric general circulation model dramatically improves simulation of the Madden–Julian oscillation (MJO) to have realistic strength, period, and propagation speed. The mechanism for the simulated MJO involves both frictional wave-convective conditional instability of the second kind (Frictional wave-CISK) and air–sea convective intraseasonal interaction (ASCII). In particular, better resolving the fine structure of upper ocean temperature, especially the warm layer, produces more vigorous atmosphere–ocean interaction and strengthens intraseasonal variations in both SST and atmospheric circulation. This helps organize and strengthen deep convection, inducing a stronger Kelvin-wave like perturbation and frictional near-surface convergence to the east. In addition, the warmer SST ahead of the MJO also acts to destabilize the boundary layer and enhance frictional convergence. These lead to a more realistic eastward-propagating MJO. A suite of sensitivity experiments were performed to show the robustness of the mechanisms and to demonstrate: (1) that mean state differences are not the main contributors to the improved simulation of our coupled model; (2) the role of SST variability in enhancing frictional convergence and intraseasonal variations in precipitation, and (3) that the simulation is significantly degraded when the first ocean model layer is thicker than 10 m. Our coupled model results are consistent with observations and demonstrate a simple but effective means to significantly improve MJO simulation and potentially also forecasts.

Process-Oriented MJO Simulation Diagnostic: Moisture Sensitivity of Simulated Convection

Abstract Process-oriented diagnostics for Madden–Julian oscillation (MJO) simulations are being developed to facilitate improvements in the representation of the MJO in weather and climate models. These process-oriented diagnostics are intended to provide insights into how parameterizations of physical processes in climate models should be improved for a better MJO simulation. This paper proposes one such process-oriented diagnostic, which is designed to represent sensitivity of simulated convection to environmental moisture: composites of a relative humidity (RH) profile based on precipitation percentiles. The ability of the RH composite diagnostic to represent the diversity of MJO simulation skill is demonstrated using a group of climate model simulations participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). A set of scalar process metrics that captures the key physical attributes of the RH diagnostic is derived and their statistical relationship with indices that quantify the fidelity of the MJO simulation is tested. It is found that a process metric that represents the amount of lower-tropospheric humidity increase required for a transition from weak to strong rain regimes has a robust statistical relationship with MJO simulation skill. The results herein suggest that moisture sensitivity of convection is closely related to a GCM’s ability to simulate the MJO.

Causal Evidence that Rotational Moisture Advection is Critical to the Superparameterized Madden–Julian Oscillation

AbstractThe authors investigate the hypothesis that horizontal moisture advection is critical to the eastward propagation of the Madden–Julian oscillation (MJO). Consistent diagnostic evidence has been found in recent MJO-permitting global models viewed from the moisture-mode dynamical paradigm. To test this idea in a causal sense, tropical moisture advection by vorticity anomalies is artificially modulated in a superparameterized global model known to produce a realistic MJO signal. Boosting horizontal moisture advection by tropical vorticity anomalies accelerates and amplifies the simulated MJO in tandem with reduced environmental gross moist stability. Limiting rotational horizontal moisture advection shuts the MJO down. These sensitivities are robust in that they are nearly monotonic with respect to the control parameter and emerge despite basic-state sensitivities favoring the opposite response. Speedup confirms what several diagnostic lines of evidence already suggest—that anomalous moisture advection is fundamental to MJO propagation. The rotational component is shown to be especially critical. Amplification further suggests it may play a role in adiabatically maintaining the MJO.

Triggered Convection, Gravity Waves, and the MJO: A Shallow-Water Model

Abstract The Madden–Julian oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics. Despite its primary importance, a generally accepted theory that accounts for fundamental features of the MJO, including its propagation speed, planetary horizontal scale, multiscale features, and quadrupole structures, remains elusive. In this study, the authors use a shallow-water model to simulate the MJO. In this model, convection is parameterized as a short-duration localized mass source and is triggered when the layer thickness falls below a critical value. Radiation is parameterized as a steady uniform mass sink. The following MJO-like signals are observed in the simulations: 1) slow eastward-propagating large-scale disturbances, which show up as low-frequency, low-wavenumber features with eastward propagation in the spectral domain, 2) multiscale structures in the time–longitude (Hovmöller) domain, and 3) quadrupole vortex structures in the longitude–latitude (map view) domain. The authors propose that the simulated MJO signal is an interference pattern of westward and eastward inertia–gravity (WIG and EIG) waves. Its propagation speed is half of the speed difference between the WIG and EIG waves. The horizontal scale of its large-scale envelope is determined by the bandwidth of the excited waves, and the bandwidth is controlled by the number density of convection events. In this model, convection events trigger other convection events, thereby aggregating into large-scale structures, but there is no feedback of the large-scale structures onto the convection events. The results suggest that the MJO is not so much a low-frequency wave, in which convection acts as a quasi-equilibrium adjustment, but is more a pattern of high-frequency waves that interact directly with the convection.

Comparison of Moist Static Energy and Budget between the GCM-Simulated Madden–Julian Oscillation and Observations over the Indian Ocean and Western Pacific

Abstract The moist static energy (MSE) anomalies and MSE budget associated with the Madden–Julian oscillation (MJO) simulated in the Iowa State University General Circulation Model (ISUGCM) over the Indian and Pacific Oceans are compared with observations. Different phase relationships between MJO 850-hPa zonal wind, precipitation, and surface latent heat flux are simulated over the Indian Ocean and western Pacific, which are greatly influenced by the convection closure, trigger conditions, and convective momentum transport (CMT). The moist static energy builds up from the lower troposphere 15–20 days before the peak of MJO precipitation, and reaches the maximum in the middle troposphere (500–600 hPa) near the peak of MJO precipitation. The gradual lower-tropospheric heating and moistening and the upward transport of moist static energy are important aspects of MJO events, which are documented in observational studies but poorly simulated in most GCMs. The trigger conditions for deep convection, obtained from the year-long cloud-resolving model (CRM) simulations, contribute to the striking difference between ISUGCM simulations with the original and modified convection schemes and play the major role in the improved MJO simulation in ISUGCM. Additionally, the budget analysis with the ISUGCM simulations shows the increase in MJO MSE is in phase with the horizontal advection of MSE over the western Pacific, while out of phase with the horizontal advection of MSE over the Indian Ocean. However, the NCEP analysis shows that the tendency of MJO MSE is in phase with the horizontal advection of MSE over both oceans.