Contributions of Convectively Coupled Equatorial Rossby Waves and Kelvin Waves to the Real-Time Multivariate MJO Indices

2009 ◽  
Vol 137 (1) ◽  
pp. 469-478 ◽  
Author(s):  
Paul E. Roundy ◽  
Carl J. Schreck ◽  
Matthew A. Janiga
Keyword(s):  
Frequency Domain ◽  
Real Time ◽  
Deep Convection ◽  
Longwave Radiation ◽  
Kelvin Waves ◽  
Wind Data ◽  
Madden Julian Oscillation ◽  
The Real ◽  
The Waves ◽  
Equatorial Rossby Waves

Abstract The real-time multivariate (RMM) Madden–Julian oscillation (MJO) indices have been widely applied to diagnose and track the progression of the MJO. Although it has been well demonstrated that the MJO contributes to the leading signals in these indices, the RMM indices vary erratically from day to day. These variations are associated with noise in the outgoing longwave radiation (OLR) and wind data used to generate the indices. This note demonstrates that some of this “noise” evolves systematically and is associated with other types of propagating modes that project onto the RMM eigenmodes. OLR and zonal wind data are filtered in the wavenumber–frequency domain for the MJO, convectively coupled equatorial Rossby (ER) waves, and convectively coupled Kelvin waves. The filtered data are then projected onto the RMM modes. An example phase space associated with these projections is presented. Linear regression is then applied to isolate the wave signals from random variations in the same bands of the wavenumber–frequency domain, and the regressed data are projected onto the RMM EOFs. Results demonstrate the magnitudes of the contributions of the systematically evolving signals associated with these waves to variations in the RMM principal components, and how these contributions vary with the longitude of the active moist deep convection coupled to the waves.

scholarly journals Observed Structure of Convectively Coupled Waves as a Function of Equivalent Depth: Kelvin Waves and the Madden–Julian Oscillation

2012 ◽  
Vol 69 (7) ◽  
pp. 2097-2106 ◽  
Author(s):  
Paul E. Roundy
Keyword(s):  
Shallow Water ◽  
Deep Convection ◽  
Longwave Radiation ◽  
Kelvin Waves ◽  
Water Model ◽  
Madden Julian Oscillation ◽  
Kelvin Wave ◽  
Easterly Wind ◽  
Equivalent Depth ◽  
Westerly Winds

Abstract The view that convectively coupled Kelvin waves and the Madden–Julian oscillation (MJO) are distinct modes is tested by regressing data from the Climate Forecast System Reanalysis against satellite outgoing longwave radiation data filtered for particular zonal wavenumbers and frequencies by wavelet analysis. Results confirm that nearly dry Kelvin waves have horizontal structures consistent with their equatorial beta-plane shallow-water-theory counterparts, with westerly winds collocated with the lower-tropospheric ridge, while the MJO and signals along Kelvin wave dispersion curves at low shallow-water-model equivalent depths are characterized by geopotential troughs extending westward from the region of lower-tropospheric easterly wind anomalies through the region of lower-tropospheric westerly winds collocated with deep convection. Results show that as equivalent depth decreases from that of the dry waves (concomitant with intensification of the associated convection), the ridge in the westerlies and the trough in the easterlies shift westward. The analysis therefore demonstrates a continuous field of intermediate structures between the two extremes, suggesting that Kelvin waves and the MJO are not dynamically distinct modes. Instead, signals consistent with Kelvin waves become more consistent with the MJO as the associated convection intensifies. This result depends little on zonal scale. Further analysis also shows how activity in synoptic-scale Kelvin waves characterized by particular phase speeds evolves with the planetary-scale MJO.

Analysis of Convectively Coupled Kelvin Waves in the Indian Ocean MJO

2008 ◽  
Vol 65 (4) ◽  
pp. 1342-1359 ◽  
Author(s):  
Paul E. Roundy
Keyword(s):  
Indian Ocean ◽  
Spatial Scales ◽  
Deep Convection ◽  
Equatorial Indian Ocean ◽  
Longwave Radiation ◽  
Kelvin Waves ◽  
Synoptic Scale ◽  
Left Behind ◽  
Geographical Regions ◽  
The Waves

Abstract The active convective phase of the Madden–Julian oscillation (hereafter active MJO) comprises enhanced moist deep convection on its own temporal and spatial scales as well as increased variance in convection associated with higher-frequency modes. Synoptic-scale cloud superclusters apparently associated with convectively coupled Kelvin waves occur within the active convective envelopes of most MJO events. These convectively coupled Kelvin waves also occur during the suppressed convective phase of the MJO (hereafter suppressed MJO). This observational study presents an analysis of outgoing longwave radiation and reanalysis data to determine how these waves behave differently as they propagate through the active and suppressed MJO. Time indices of the MJO and Kelvin waves are derived for over the equatorial Indian Ocean. Dates of local extrema in these indices are used to composite data to discern how the waves and associated circulations behave on average; then, further composites are made based on subsets of this list of dates that are consistent with the two MJO phases. Results show that the MJO phase modulates the intensity of moist deep convection associated with the Kelvin waves, the evolution of the vertical structure of cloudiness linked to Kelvin waves, and patterns of upper-level outflow from convection coupled to Kelvin waves. Composites reveal that synoptic-scale circulations associated with the release of latent heat in convection coupled to Kelvin waves amplify and are left behind the waves in preferred geographical regions. The MJO modulates the amplitudes of these circulations and the locations where they get left behind the waves. Previous results have suggested a sharp distinction between the phase speeds of the MJO (4–8 m s−1) and of convectively coupled Kelvin waves (specifically 17 m s−1). In contrast, the present work suggests that convectively coupled Kelvin waves have a broad range of characteristic phase speeds, extending from 10 to 17 m s−1, depending on both the region of the world and the phase of the MJO through which they propagate.

scholarly journals Equatorial Waves Including the Madden–Julian Oscillation in TRMM Rainfall and OLR Data

2004 ◽  
Vol 17 (22) ◽  
pp. 4387-4406 ◽  
Author(s):  
Hye-Kyung Cho ◽  
Kenneth P. Bowman ◽  
Gerald R. North
Keyword(s):  
Large Scale ◽  
Longwave Radiation ◽  
Tropical Rainfall Measuring Mission ◽  
Space Time ◽  
Madden Julian Oscillation ◽  
Limited Sampling ◽  
The Tropics ◽  
The Waves ◽  
Section Analysis ◽  
Equatorial Rossby Waves

Abstract Four years of outgoing longwave radiation (OLR) and rainfall data from the Tropical Rainfall Measuring Mission (TRMM) are investigated to find the dominant large-scale wave modes in the Tropics. By using space– time cross-section analysis and spectral analysis, the longitudinal and latitudinal behaviors of the overall waves and the dominant waves are observed. Despite the noisy nature of precipitation data and the limited sampling by the TRMM satellite, pronounced peaks are found for Kelvin waves, n = 1 equatorial Rossby waves (ER), and mixed Rossby–gravity waves (MRG). Madden–Julian oscillation (MJO) and tropical depression (TD)-type disturbances are also detected. The seasonal evolution of these waves is investigated. An appendix includes a study of sampling and aliasing errors due to the peculiar space–time sampling pattern of TRMM. It is shown that the waves detected in this study are not artifacts of these sampling features. The results presented here are compared with previous studies. Consistency with their results gives confidence in the TRMM data for wave studies. The results from this study can be utilized for modeling and testing theories. Also, it may be useful for the future users of the TRMM data to understand the nature of the TRMM satellite sampling.

scholarly journals The Spectrum of Convectively Coupled Kelvin Waves and the Madden–Julian Oscillation in Regions of Low-Level Easterly and Westerly Background Flow

2012 ◽  
Vol 69 (7) ◽  
pp. 2107-2111 ◽  
Author(s):  
Paul E. Roundy
Keyword(s):  
Longwave Radiation ◽  
Wave Dispersion ◽  
Warm Pool ◽  
Kelvin Waves ◽  
Madden Julian Oscillation ◽  
Westerly Wind ◽  
Kelvin Wave ◽  
Low Level ◽  
Geographical Regions ◽  
Zonal Wavenumber

Abstract The zonal wavenumber–frequency power spectrum of outgoing longwave radiation in the global tropics suggests that power in convectively coupled Kelvin waves and the Madden–Julian oscillation (MJO) is organized into two distinct spectral peaks with a minimum in power in between. This work demonstrates that integration of wavelet power in the wavenumber–frequency domain over geographical regions of moderate trade winds yields a similar pronounced spectral gap between these peaks. In contrast, integration over regions of background low-level westerly wind yields a continuum of power with no gap between the MJO and Kelvin bands. Results further show that signals in tropical convection are redder in frequency in these low-level westerly wind zones, confirming that Kelvin waves tend to propagate more slowly eastward over the warm pool than other parts of the world. Results are consistent with the perspective that portions of disturbances labeled as Kelvin waves and the MJO that are proximate to Kelvin wave dispersion curves exist as a continuum over warm pool regions.

scholarly journals Oceanic Impetus for Convective Onset of the Madden–Julian Oscillation in the Western Indian Ocean

2017 ◽  
Vol 30 (11) ◽  
pp. 4299-4316 ◽  
Author(s):  
Adam V. Rydbeck ◽  
Tommy G. Jensen
Keyword(s):  
Boundary Layer ◽  
Indian Ocean ◽  
Atmospheric Boundary Layer ◽  
Rossby Waves ◽  
Deep Convection ◽  
Western Indian Ocean ◽  
Convection Boundary Layer ◽  
Madden Julian Oscillation ◽  
Sst Gradient ◽  
Equatorial Rossby Waves

Abstract A theory for intraseasonal atmosphere–ocean–atmosphere feedback is supported whereby oceanic equatorial Rossby waves are partly forced in the eastern Indian Ocean by the Madden–Julian oscillation (MJO), reemerge in the western Indian Ocean ~70 days later, and force large-scale convergence in the atmospheric boundary layer that precedes MJO deep convection. Downwelling equatorial Rossby waves permit high sea surface temperature (SST) and enhance meridional and zonal SST gradients that generate convergent circulations in the atmospheric boundary layer. The magnitude of the SST and SST gradient increases are 0.25°C and 1.5°C Mm−1 (1 megameter is equal to 1000 km), respectively. The atmospheric circulations driven by the SST gradient are estimated to be responsible for up to 45% of the intraseasonal boundary layer convergence observed in the western Indian Ocean. The SST-induced boundary layer convergence maximizes 3–4 days prior to the convective maximum and is hypothesized to serve as a trigger for MJO deep convection. Boundary layer convergence is shown to further augment deep convection by locally increasing boundary layer moisture. Warm SST anomalies facilitated by downwelling equatorial Rossby waves are also associated with increased surface latent heat fluxes that occur after MJO convective onset. Finally, generation of the most robust downwelling equatorial Rossby waves in the western Indian Ocean is shown to have a distinct seasonal distribution.

scholarly journals PENGEMBANGAN MODEL PREDIKSI MADDEN JULIAN OSCILLATION (MJO) BERBASIS PADA HASIL ANALISIS DATA REAL TIME MULTIVARIATE MJO (RMM1 DAN RMM2) (PREDICTION MODEL DEVELOPMENT MADDEN JULIAN OSCILLATION (MJO) BASED ON THE RESULTS OF DATA ANALYSIS ...

Agromet ◽  
2008 ◽  
Vol 22 (2) ◽  
pp. 144 ◽  
Author(s):  
Lisa Evana ◽  
Sobri Effendy ◽  
Eddy Hermawan
Keyword(s):  
Prediction Model ◽  
Real Time ◽  
Outgoing Longwave Radiation ◽  
Time Series Data ◽  
Longwave Radiation ◽  
Empirical Orthogonal Functions ◽  
Wave Radiation ◽  
Series Data ◽  
Madden Julian Oscillation ◽  
Coverage Area

Background of this research is the importance of study on the Madden Julian Oscillation, the dominant oscillation in the equator area. MJO cycle showed by cloud cluster growing in the Indian Ocean then moved to the east and form a cycle with a range of 40-50 days and the coverage area from 10N-10S. Method that used to predict RMM is Box-Jenkins based on ARIMA (Autoregressive Integrated Moving Average) statistical analysis. The data used RMM daily data period 1 Maret 1979–1 Maret 2009 (30 years). RMM1 and RMM2 is an index for monitoring MJO. This is based on two empirical orthogonal functions (EOFs) from the combined average zonal 850hPa wind, 200hPa zonal wind, and satellite-observed Outgoing Longwave Radiation (OLR) data. The results in form of the Power Spectral Density (PSD) graph Real Time Multivariate MJO (RMM) and long wave radiation (OLR = Outgoing Longwave Radiation) at the position 100° BT, 120° BT, and 140°BT that show the wave pattern (spectrum pattern) and clearly shows the oscillation periods. There is a close relation between RMM1 with OLR at the position 100oBT that characterized the PSD value about 45 day. Through Box-Jenkins method, the prediction model that close to time series data of RMM1 and RMM2 is ARIMA (2,1,2), that mean the forecasts of RMM data for the future depending on one time previously and the error one time before. Prediction model for Zt = Zt = 1,681 Zt-1 – 0,722 Zt-2 - 0,02 at-1 - 0,05 at-2.. Prediction model for RMM2 is Zt = 1,714 Zt-1 – 0,764 Zt-2 - 0,109 at-1 - 0,05 at-2.. The flood case in Jakarta January-February 1996 and 2002 are one of real evidence that made the MJO prediction important. MJO with active phase dominant cover almost the entire Indonesia west area at that moment.

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

2015 ◽  
Vol 143 (6) ◽  
pp. 2148-2169 ◽  
Author(s):  
Nan Chen ◽  
Andrew J. Majda
Keyword(s):  
Stochastic Model ◽  
Real Time ◽  
Stochastic Models ◽  
Multiplicative Noise ◽  
Hidden Variables ◽  
Ensemble Prediction ◽  
Madden Julian Oscillation ◽  
The Real ◽  
Nonlinear Stochastic Model ◽  
Low Order

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.

Predictability of the Madden–Julian Oscillation Estimated Using Observational Data

2010 ◽  
Vol 138 (3) ◽  
pp. 1004-1013 ◽  
Author(s):  
Ruiqiang Ding ◽  
Jianping Li ◽  
Kyong-Hwan Seo
Keyword(s):  
Real Time ◽  
Observational Data ◽  
Numerical Models ◽  
Longwave Radiation ◽  
Large Error ◽  
Madden Julian Oscillation ◽  
Wind Fields ◽  
Potential Predictability ◽  
Time Prediction ◽  
Real Time Analysis

Abstract Existing numerical models produce large error in simulating the Madden–Julian oscillation (MJO), thereby underestimating its predictability. In this paper, the predictability limit of the MJO is determined by the nonlinear local Lyapunov exponent approach, which provides an estimate of atmospheric predictability based on the observational data. The results show that the predictability limit of the MJO obtained from the bandpass-filtered (30–80 days) outgoing longwave radiation and wind fields, which serves as an empirical estimate of the theoretical potential predictability of the MJO, can exceed 5 weeks, which is well above the 1-week predictability of background noise caused by bandpass filtering. In contrast, a real-time analysis of MJO predictability using the real-time multivariate MJO (RMM) index, as introduced by Wheeler and Hendon, reveals a predictability limit of about 3 weeks. The findings reported here raise the possibility of obtaining a higher predictability limit in real-time prediction by improving the RMM index or by introducing a better method of extracting intraseasonal signals.

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