Predictability of the Madden–Julian Oscillation in the Intraseasonal Variability Hindcast Experiment (ISVHE)*

2014 ◽  
Vol 27 (12) ◽  
pp. 4531-4543 ◽  
Author(s):  
J. M. Neena ◽  
June Yi Lee ◽  
Duane Waliser ◽  
Bin Wang ◽  
Xianan Jiang
Keyword(s):  
Dynamic Models ◽  
Intraseasonal Variability ◽  
Prediction Skill ◽  
Ensemble Prediction ◽  
Future Research ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Maritime Continent ◽  
Coupled Models ◽  
Ensemble Mean

Abstract The Madden–Julian oscillation (MJO) represents a primary source of predictability on the intraseasonal time scales and its influence extends from seasonal variations to weather and extreme events. While the last decade has witnessed marked improvement in dynamical MJO prediction, an updated estimate of MJO predictability from a contemporary suite of dynamic models, in conjunction with an estimate of their corresponding prediction skill, is crucial for guiding future research and development priorities. In this study, the predictability of the boreal winter MJO is revisited based on the Intraseasonal Variability Hindcast Experiment (ISVHE), a set of dedicated extended-range hindcasts from eight different coupled models. Two estimates of MJO predictability are made, based on single-member and ensemble-mean hindcasts, giving values of 20–30 days and 35–45 days, respectively. Exploring the dependence of predictability on the phase of MJO during hindcast initiation reveals a slightly higher predictability for hindcasts initiated from MJO phases 2, 3, 6, or 7 in three of the models with higher prediction skill. The estimated predictability of MJO initiated in phases 2 and 3 (i.e., convection in Indian Ocean with subsequent propagation across Maritime Continent) being equal to or higher than other MJO phases implies that the so-called Maritime Continent prediction barrier may not actually be an intrinsic predictability limitation. For most of the models, the skill for single-member (ensemble mean) hindcasts is less than the estimated predictability limit by about 5–10 days (15–25 days), implying that significantly more skillful MJO forecasts can be afforded through further improvements of dynamical models and ensemble prediction systems (EPS).

scholarly journals Impacts of the Tropical Pacific–Indian Ocean Associated Mode on Madden–Julian Oscillation over the Maritime Continent in Boreal Winter

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1049
Author(s):  
Xin Li ◽  
Ming Yin ◽  
Xiong Chen ◽  
Minghao Yang ◽  
Fei Xia ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Kinetic Energy ◽  
Tropical Pacific ◽  
Western Pacific ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Maritime Continent ◽  
The Western Pacific ◽  
The Tropical Pacific

Based on the observation and reanalysis data, the relationship between the Madden–Julian Oscillation (MJO) over the Maritime Continent (MC) and the tropical Pacific–Indian Ocean associated mode was analyzed. The results showed that the MJO over the MC region (95°–150° E, 10° S–10° N) (referred to as the MC–MJO) possesses prominent interannual and interdecadal variations and seasonally “phase-locked” features. MC–MJO is strongest in the boreal winter and weakest in the boreal summer. Winter MC–MJO kinetic energy variation has significant relationships with the El Niño–Southern Oscillation (ENSO) in winter and the Indian Ocean Dipole (IOD) in autumn, but it correlates better with the tropical Pacific–Indian Ocean associated mode (PIOAM). The correlation coefficient between the winter MC–MJO kinetic energy index and the autumn PIOAM index is as high as −0.5. This means that when the positive (negative) autumn PIOAM anomaly strengthens, the MJO kinetic energy over the winter MC region weakens (strengthens). However, the correlation between the MC–MJO convection and PIOAM in winter is significantly weaker. The propagation of MJO over the Maritime Continent differs significantly in the contrast phases of PIOAM. During the positive phase of the PIOAM, the eastward propagation of the winter MJO kinetic energy always fails to move across the MC region and cannot enter the western Pacific. However, during the negative phase of the PIOAM, the anomalies of MJO kinetic energy over the MC is not significantly weakened, and MJO can propagate farther eastward and enter the western Pacific. It should be noted that MJO convection is more likely to extend to the western Pacific in the positive phases of PIOAM than in the negative phases. This is significant different with the propagation of the MJO kinetic energy.

scholarly journals Indications for a potential synchronization between the phase evolution of the Madden–Julian oscillation and the solar 27-day cycle

2019 ◽  
Vol 19 (7) ◽  
pp. 4235-4256 ◽  
Author(s):  
Christoph G. Hoffmann ◽  
Christian von Savigny
Keyword(s):  
Time Lag ◽  
Intraseasonal Variability ◽  
Longwave Radiation ◽  
Phase Evolution ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Atmospheric Conditions ◽  
Quasi Biennial Oscillation ◽  
Open Questions ◽  
Solid Foundation

Abstract. The Madden–Julian oscillation (MJO) is a major source of intraseasonal variability in the troposphere. Recently, studies have indicated that also the solar 27-day variability could cause variability in the troposphere. Furthermore, it has been indicated that both sources could be linked, and particularly that the occurrence of strong MJO events could be modulated by the solar 27-day cycle. In this paper, we analyze whether the temporal evolution of the MJO phases could also be linked to the solar 27-day cycle. We basically count the occurrences of particular MJO phases as a function of time lag after the solar 27-day extrema in about 38 years of MJO data. Furthermore, we develop a quantification approach to measure the strength of such a possible relationship and use this to compare the behavior for different atmospheric conditions and different datasets, among others. The significance of the results is estimated based on different variants of the Monte Carlo approach, which are also compared. We find indications for a synchronization between the MJO phase evolution and the solar 27-day cycle, which are most notable under certain conditions: MJO events with a strength greater than 0.5, during the easterly phase of the quasi-biennial oscillation, and during boreal winter. The MJO appears to cycle through its eight phases within two solar 27-day cycles. The phase relation between the MJO and the solar variation appears to be such that the MJO predominantly transitions from phase 8 to 1 or from phase 4 and 5 during the solar 27-day minimum. These results strongly depend on the MJO index used such that the synchronization is most clearly seen when using univariate indices like the OLR-based MJO index (OMI) in the analysis but can hardly be seen with multivariate indices like the real-time multivariate MJO index (RMM). One possible explanation could be that the synchronization pattern is encoded particularly in the underlying outgoing longwave radiation (OLR) data. A weaker dependence of the results on the underlying solar proxy is also observed but not further investigated. Although we think that these initial indications are already worth noting, we do not claim to unambiguously prove this relationship in the present study, neither in a statistical nor in a causal sense. Instead, we challenge these initial findings ourselves in detail by varying underlying datasets and methods and critically discuss resulting open questions to lay a solid foundation for further research.

scholarly journals Toward a better multi-model ensemble prediction of East Asian and Australasian precipitation during non-mature ENSO seasons

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Soo-Jin Sohn ◽  
WonMoo Kim
Keyword(s):  
Southern Oscillation ◽  
East Asian ◽  
Precipitation Variability ◽  
Prediction Skill ◽  
Ensemble Prediction ◽  
Boreal Winter ◽  
Model Ensemble ◽  
Boreal Spring ◽  
Mature Phase ◽  
Regional Prediction

AbstractAn effective and reliable way for better predicting the seasonal Australasian and East Asian precipitation variability in a multi-model ensemble (MME) prediction system is newly designed, in relation to the performance of predicting El Niño-Southern Oscillation (ENSO) and its impact. While ENSO is a major predictability source of global and regional precipitation variation, the prediction skill of precipitation is not solely due to typical ENSO alone, of which variability and predictability exhibit strong seasonality. The first mode of ENSO variability has large variance with high prediction skill for boreal winter and small variance with low skill for spring and summer, while the second mode shows the opposite phase. The regional prediction skills for Australasian and East Asian precipitation also show such seasonal dependence, with low skill and large spread of individual models’ skills during the boreal spring to summer and high skill and small spread during winter. Using the individual models’ reproducibility of the association between ENSO and regional precipitation, the prediction skills of the MME with selected models can improve at regional levels, compared to those for all-inclusive MME, during boreal spring to summer. While typical ENSO as a predictability source may still dominate during boreal winter, consideration of complex ENSO structure and its diverse impact can lead to a better prediction of regional precipitation variability during non-mature phase of ENSO seasons.

A large ensemble decadal prediction system with MPI-ESM

2021 ◽  
Author(s):  
Sebastian Brune ◽  
Vimal Koul ◽  
David Marcolino Nielsen ◽  
Laura Hövel ◽  
Holger Pohlmann ◽  
...  
Keyword(s):  
North Atlantic ◽  
Prediction Skill ◽  
Ensemble Prediction ◽  
Prediction System ◽  
Decadal Prediction ◽  
Ensemble Size ◽  
Large Ensemble ◽  
Ensemble Prediction System ◽  
Atlantic Sector ◽  
Ensemble Mean

<p>Current state-of-the-art decadal ensemble prediction systems are run with an ensemble size of 10 to 40 members, their retrospective forecasts of the past are used to assess the system's prediction skill. Here, we present an attempt for a large ensemble decadal prediction system for the time period 1960-today, with an ensemble size of 80 members, based on the low resolution version of the Max Planck Institute Earth system model (MPI-ESM-LR). The ensemble is forced with CMIP6 conditions and initialized every year in November through a weakly coupled assimilation using atmospheric reanalyses via nudging and observed oceanic temperature and salinity profiles via a 16-member ensemble Kalman filter. To generate ensemble members beyond 16, we use additional physical perturbations at stratospheric height. The analysis of our large ensemble prediction system presented here aims for answering two questions: (1) How does the ensemble mean deterministic prediction skill for global and North Atlantic key climate indices change with ensemble size? (2) How well may the 80-member ensemble serve as a basis for a robust statistical analysis of probabilities of extremes in the North Atlantic sector? Preliminary results for global and regional air surface temperature show that in terms of ensemble mean ACC and full ensemble CPRSS with reference data, the 80-member ensemble leads to similar prediction skill as the 16-member ensemble. This indicates that the additional ensemble members may lead to a better sampling of the distribution of model trajectories, paving the way for a more robust statistical probabilistic analysis.</p>

Assessing Predictive Potential Associated with the MJO during the Boreal Winter

2020 ◽  
Vol 148 (12) ◽  
pp. 4957-4969
Author(s):  
Arun Kumar ◽  
Jieshun Zhu ◽  
Wanqiu Wang
Keyword(s):  
Surface Temperature ◽  
Observational Data ◽  
Prediction Skill ◽  
Meteorological Variables ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Potential Predictability ◽  
Upper Limit ◽  
Prediction Systems ◽  
A Chain

AbstractIn this paper, the question of potential predictability in meteorological variables associated with skillful prediction of the Madden–Julian oscillation (MJO) during boreal winter is analyzed. The analysis is motivated by the fact that dynamical prediction systems are now capable of predicting MJO up to 30 days or earlier (measured in terms of anomaly correlation for RMM indices). Translating recent gains in MJO prediction skill and relating them back to potential for predicting meteorological variables—for example, precipitation and surface temperature—is not straightforward because of a chain of steps that go into the computation and evaluation of RMM indices. This paper assesses potential predictability in meteorological variables that could be attributed to skillful prediction of the MJO. The analysis is based on the observational data alone and assesses the upper limit of MJO-associated predictability that could be achieved.

The 3–4-Week MJO Prediction Skill in a GFDL Coupled Model

2015 ◽  
Vol 28 (13) ◽  
pp. 5351-5364 ◽  
Author(s):  
Baoqiang Xiang ◽  
Ming Zhao ◽  
Xianan Jiang ◽  
Shian-Jiann Lin ◽  
Tim Li ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Strong Dependence ◽  
Intraseasonal Variability ◽  
Coupled Model ◽  
Prediction Skill ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Madden Julian Oscillation ◽  
Geophysical Fluid Dynamics ◽  
Potential Predictability ◽  
Anomaly Correlation Coefficient

Abstract Based on a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the Madden–Julian oscillation (MJO) prediction skill in boreal wintertime (November–April) is evaluated by analyzing 11 years (2003–13) of hindcast experiments. The initial conditions are obtained by applying a simple nudging technique toward observations. Using the real-time multivariate MJO (RMM) index as a predictand, it is demonstrated that the MJO prediction skill can reach out to 27 days before the anomaly correlation coefficient (ACC) decreases to 0.5. The MJO forecast skill also shows relatively larger contrasts between target strong and weak cases (32 versus 7 days) than between initially strong and weak cases (29 versus 24 days). Meanwhile, a strong dependence on target phases is found, as opposed to relative skill independence from different initial phases. The MJO prediction skill is also shown to be about 29 days during the Dynamics of the MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (DYNAMO/CINDY) field campaign period. This model’s potential predictability, the upper bound of prediction skill, extends out to 42 days, revealing a considerable unutilized predictability and a great potential for improving current MJO prediction.

scholarly journals Effects of Surface Orography and Land–Sea Contrast on the Madden–Julian Oscillation in the Maritime Continent: A Numerical Study Using ECHAM5-SIT

2017 ◽  
Vol 30 (23) ◽  
pp. 9725-9741 ◽  
Author(s):  
Wan-Ling Tseng ◽  
Huang-Hsiung Hsu ◽  
Noel Keenlyside ◽  
Chiung-Wen June Chang ◽  
Ben-Jei Tsuang ◽  
...  
Keyword(s):  
General Circulation ◽  
Numerical Study ◽  
Empirical Studies ◽  
Circulation Model ◽  
Wave Structure ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Maritime Continent ◽  
Zonal Scale ◽  
Accurate Forecast

This study uses the atmospheric general circulation model (AGCM) ECHAM5 coupled with the newly developed Snow–Ice–Thermocline model (ECHAM5-SIT) to examine the effects of orography and land–sea contrast on the Madden–Julian oscillation (MJO) in the Maritime Continent (MC) during boreal winter. The ECHAM5-SIT is one of the few AGCMs that realistically simulate the major characteristics of the MJO. Three experiments are conducted with realistic topography, without orography, and with oceans only in the MC region to evaluate the relative effects of orography and land–sea contrast. Orography and land–sea contrast have the following effects on the MJO in the MC: 1) a larger amplitude, 2) a smaller zonal scale, 3) more realistic periodicity and stronger eastward-propagating signals, 4) a stronger southward detour during the eastward propagation, 5) a distorted coupled Kelvin–Rossby wave structure, and 6) larger low-level moisture convergence. The existence of mountainous islands also enhances the mean westerly in the eastern Indian Ocean and the western MC, as well as the moisture content over the MC. This enhancement of mean states contributes to the stronger eastward-propagating MJO. The findings herein suggest that theoretical and empirical studies, which are largely derived from an aquaplanet framework, have likely provided an oversimplified view of the MJO. The effects of mountainous islands should be considered for better understanding and more accurate forecast of the MJO.

scholarly journals Stratospheric Control of the Madden–Julian Oscillation

2017 ◽  
Vol 30 (6) ◽  
pp. 1909-1922 ◽  
Author(s):  
Seok-Woo Son ◽  
Yuna Lim ◽  
Changhyun Yoo ◽  
Harry H. Hendon ◽  
Joowan Kim
Keyword(s):  
El Niño ◽  
Interannual Variation ◽  
El Nino ◽  
Southern Oscillation ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Maritime Continent ◽  
Quasi Biennial Oscillation ◽  
Tropospheric Circulation ◽  
Biennial Oscillation

Abstract Interannual variation of seasonal-mean tropical convection over the Indo-Pacific region is primarily controlled by El Niño–Southern Oscillation (ENSO). For example, during El Niño winters, seasonal-mean convection around the Maritime Continent becomes weaker than normal, while that over the central to eastern Pacific is strengthened. Similarly, subseasonal convective activity, which is associated with the Madden–Julian oscillation (MJO), is influenced by ENSO. The MJO activity tends to extend farther eastward to the date line during El Niño winters and contract toward the western Pacific during La Niña winters. However, the overall level of MJO activity across the Maritime Continent does not change much in response to the ENSO. It is shown that the boreal winter MJO amplitude is closely linked with the stratospheric quasi-biennial oscillation (QBO) rather than with ENSO. The MJO activity around the Maritime Continent becomes stronger and more organized during the easterly QBO winters. The QBO-related MJO change explains up to 40% of interannual variation of the boreal winter MJO amplitude. This result suggests that variability of the MJO and the related tropical–extratropical teleconnections can be better understood and predicted by taking not only the tropospheric circulation but also the stratospheric mean state into account. The seasonality of the QBO–MJO link and the possible mechanism are also discussed.

scholarly journals Intraseasonal Variability of δ18O of Precipitation over the Indonesian Maritime Continent Related to the Madden–Julian Oscillation

SOLA ◽  
2016 ◽  
Vol 12 (0) ◽  
pp. 192-197 ◽  
Author(s):  
Halda A. Belgaman ◽  
Kimpei Ichiyanagi ◽  
Masahiro Tanoue ◽  
Rusmawan Suwarman ◽  
Kei Yoshimura ◽  
...  
Keyword(s):  
Intraseasonal Variability ◽  
Madden Julian Oscillation ◽  
Maritime Continent

A Multiscale Model for the Intraseasonal Impact of the Diurnal Cycle over the Maritime Continent on the Madden–Julian Oscillation

2016 ◽  
Vol 73 (2) ◽  
pp. 579-604 ◽  
Author(s):  
Andrew J. Majda ◽  
Qiu Yang
Keyword(s):  
Diurnal Cycle ◽  
Numerical Models ◽  
Multiscale Model ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Maritime Continent ◽  
Upper Troposphere ◽  
Planetary Scale ◽  
Baroclinic Modes ◽  
Huge Challenge

Abstract The eastward-propagating Madden–Julian oscillation (MJO) typically exhibits complex behavior during its passage over the Maritime Continent, sometimes slowly propagating eastward and other times stalling and even terminating there with large amounts of rainfall. This is a huge challenge for present-day numerical models to simulate. One possible reason is the inadequate treatment of the diurnal cycle and its scale interaction with the MJO. Here these two components are incorporated into a simple self-consistent multiscale model that includes one model for the intraseasonal impact of the diurnal cycle and another one for the planetary/intraseasonal circulation. The latter model is forced self-consistently by eddy flux divergences of momentum and temperature from a model for the diurnal cycle with two baroclinic modes, which capture the intraseasonal impact of the diurnal cycle. The MJO is modeled as the planetary-scale circulation response to a moving heat source on the synoptic and planetary scales. The results show that the intraseasonal impact of the diurnal cycle during boreal winter tends to strengthen the westerlies (easterlies) in the lower (upper) troposphere in agreement with the observations. In addition, the temperature anomaly induced by the intraseasonal impact of the diurnal cycle can cancel that from the symmetric–asymmetric MJO with convective momentum transfer, yielding stalled or suppressed propagation of the MJO across the Maritime Continent. The simple multiscale model should be useful for the MJO in observations or more complex numerical models.

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