A Systematic Relationship between the Representations of Convectively Coupled Equatorial Wave Activity and the Madden–Julian Oscillation in Climate Model Simulations

2015 ◽  
Vol 28 (5) ◽  
pp. 1881-1904 ◽  
Author(s):  
Yanjuan Guo ◽  
Duane E. Waliser ◽  
Xianan Jiang
Keyword(s):  
High Frequency ◽  
General Circulation ◽  
Large Scale ◽  
Task Force ◽  
General Circulation Models ◽  
Madden Julian Oscillation ◽  
Frequency Wave ◽  
High Frequency Wave ◽  
Equatorial Wave ◽  
Wave Modes

Abstract The relationship between a model’s performance in simulating the Madden–Julian oscillation (MJO) and convectively coupled equatorial wave (CCEW) activity during wintertime is examined by analyzing precipitation from 26 general circulation models (GCMs) participating in the MJO Task Force/Global Energy and Water Cycle Experiment (GEWEX) Atmospheric System Study (GASS) MJO model intercomparison project as well as observations based on the Tropical Rainfall Measuring Mission (TRMM). A model’s performance in simulating the MJO is determined by how faithfully it reproduces the eastward propagation of the large-scale intraseasonal variability (ISV) compared to TRMM observations. Results suggest that models that simulate a better MJO tend to 1) have higher fractional variances for various high-frequency wave modes (Kelvin, mixed Rossby–gravity, and westward and eastward inertio-gravity waves), which are defined by the ratios of wave variances of specific wave modes to the “total” variance, and 2) exhibit stronger CCEW variances in association with the eastward-propagating ISV precipitation anomalies for these high-frequency wave modes. The former result is illustrative of an alleviation in the good MJO models of the widely reported GCM deficiency in simulating the correct distribution of variance in tropical convection [i.e., typically too weak (strong) variance in the high- (low-) frequency spectrum of the precipitation]. The latter suggests better coherence and stronger interactions between these aforementioned high-frequency CCEWs and the ISV envelope in good MJO models. Both factors likely contribute to the improved simulation of the MJO in a GCM.

A Model for Scale Interaction in the Madden–Julian Oscillation*

2011 ◽  
Vol 68 (11) ◽  
pp. 2524-2536 ◽  
Author(s):  
Bin Wang ◽  
Fei Liu
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Circulation System ◽  
Stationary Mode ◽  
Madden Julian Oscillation ◽  
Scale Interaction ◽  
Planetary Scale ◽  
Equatorial Wave

Abstract The Madden–Julian oscillation (MJO) is an equatorial planetary-scale circulation system coupled with a multiscale convective complex, and it moves eastward slowly (about 5 m s−1) with a horizontal quadrupole vortex and vertical rearward-tilted structure. The nature and role of scale interaction (SI) is one of the elusive aspects of the MJO dynamics. Here a prototype theoretical model is formulated to advance the current understanding of the nature of SI in MJO dynamics. The model integrates three essential physical elements: (a) large-scale equatorial wave dynamics driven by boundary layer frictional convergence instability (FCI), (b) effects of the upscale eddy momentum transfer (EMT) by vertically tilted synoptic systems resulting from boundary layer convergence and multicloud heating, and (c) interaction between planetary-scale wave motion and synoptic-scale systems (the eastward-propagating super cloud clusters and westward-propagating 2-day waves). It is shown that the EMT mechanism tends to yield a stationary mode with a quadrupole vortex structure (enhanced Rossby wave component), whereas the FCI yields a relatively fast eastward-moving and rearward-tilted Gill-like pattern (enhanced Kelvin wave response). The SI instability stems from corporative FCI or EMT mechanisms, and its property is a mixture of FCI and EMT modes. The properties of the unstable modes depend on the proportion of deep convective versus stratiform/congestus heating or the ratio of deep convective versus total amount of heating. With increasing stratiform/congestus heating, the FCI weakens while the EMT becomes more effective. A growing SI mode has a horizontal quadrupole vortex and rearward-tilted structure and prefers slow eastward propagation, which resembles the observed MJO. The FCI sets the rearward tilt and eastward propagation, while the EMT slows down the propagation speed. The theoretical results presented here point to the need to observe multicloud structure and vertical heating profiles within the MJO convective complex and to improve general circulation models’ capability to reproduce correct partitioning of cloud amounts between deep convective and stratiform/congestus clouds. Limitations and future work are also discussed.

A Frictional Skeleton Model for the Madden–Julian Oscillation*

2012 ◽  
Vol 69 (9) ◽  
pp. 2749-2758 ◽  
Author(s):  
Fei Liu ◽  
Bin Wang
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Madden Julian Oscillation ◽  
Ekman Pumping ◽  
Convective Envelope ◽  
Skeleton Model ◽  
Planetary Scale ◽  
System A ◽  
Frictional Convergence

Abstract The Madden–Julian oscillation (MJO) is a multiscale system. A skeleton model, developed by Majda and Stechmann, can capture some of planetary-scale aspects of observed features such as slow eastward propagation, nondispersive behavior, and quadrupole-vortex structure. However, the Majda–Stechmann model cannot explain the source of instability and the preferred planetary scale of the MJO. Since the MJO major convection region is leaded by its planetary boundary layer (PBL) moisture convergence, here a frictional skeleton model is built by implementing a slab PBL into the neutral skeleton model. As a skeleton model allowing the scale interaction, this model is only valid for large-scale waves. This study shows that the PBL frictional convergence provides a strong instability source for the long eastward modes, although it also destabilizes very short westward modes. For the long waves (wavenumber less than 5), the PBL Ekman pumping moistens the low troposphere to the east of the MJO convective envelope, and sets up favorable moist conditions to destabilize the MJO and favor only eastward modes. Sensitivity experiments show that a weak PBL friction will enhance the instability slightly. The sea surface temperature (SST) with a maximum at the equator also prefers the long eastward modes. These theoretical analysis results encourage further observations on the PBL regulation of mesosynoptic-scale motions, and exploration of the interaction between PBL and multiscale motions, associated with the MJO to improve the MJO simulation in general circulation models (GCMs).

scholarly journals Research of the process of vegetable oil extracting under the influence of a high frequency wave field

2020 ◽  
Vol 941 ◽  
pp. 012052
Author(s):  
V Yu Ovsyannikov ◽  
A A Berestovoy ◽  
N N Lobacheva ◽  
V V Toroptsev ◽  
S A Trunov
Keyword(s):  
Wave Field ◽  
Vegetable Oil ◽  
High Frequency ◽  
Frequency Wave ◽  
High Frequency Wave

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

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