Special Issue "Madden-Julian Oscillation"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology and Meteorology".

Deadline for manuscript submissions: closed (31 August 2017).

Special Issue Editor

Guest Editor
Prof. Dr. Charles Jones Website E-Mail
Department of Geography and Earth Research Institute (ERI),University of California, Santa Barbara, CA 93106-3060, USA
Interests: precipitation variability, extreme events, weather forecasts, predictability studies, regional modeling, monsoon systems, and climate change

Special Issue Information

Dear Colleagues,

The Madden-Julian Oscillation (MJO) is the most important mode of tropical intraseasonal variability. The MJO influences precipitation and temperature variability in the tropics, as well as extratropics and high laititudes of both hemispheres. The influential nature of the MJO has also been noted on occurrences of extreme weather events, accuracy of weather forecasts, interactions with El Niño/Southern Oscillation (ENSO), deep ocean variability, distributions of tropical cyclones and hurricanes, tropospheric ozone changes, surface chlorophyll, and phytoplankton variations in tropical oceans and coastal areas. The oscillation exhibits important seasonal changes and pronounced interannual and multi-year variations. This Special Issue invites original research papers dealing with any aspects related to the MJO and its role in weather and climate variability. Review papers are also welcome.

Prof. Charles Jones
Guest Editor

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Published Papers (10 papers)

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Editorial

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Open AccessEditorial
Madden–Julian Oscillation
Atmosphere 2018, 9(3), 100; https://doi.org/10.3390/atmos9030100 - 11 Mar 2018
Abstract
The Madden–Julian Oscillation (MJO) is the most important mode of tropical intraseasonal variability. [...] Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)

Research

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Open AccessArticle
The 30–50-Day Intraseasonal Oscillation of SST and Precipitation in the South Tropical Indian Ocean
Atmosphere 2018, 9(2), 69; https://doi.org/10.3390/atmos9020069 - 15 Feb 2018
Cited by 1
Abstract
The Sea Surface Temperature (SST) in the South Tropical Indian Ocean (STIO) displays significant intraseasonal oscillation (ISO) in two regions. A striking 30–50-day ISO found over the east of thermocline ridge (Region A, 80–90° E, 6–12° S), as identified by the Empirical Mode [...] Read more.
The Sea Surface Temperature (SST) in the South Tropical Indian Ocean (STIO) displays significant intraseasonal oscillation (ISO) in two regions. A striking 30–50-day ISO found over the east of thermocline ridge (Region A, 80–90° E, 6–12° S), as identified by the Empirical Mode Decomposition (EMD) method, is distinguished from the SST signature over the thermocline ridge (Region B, 52.5–65° E, 6–13° S). The 30–50-day ISO of SST in the Region A is active in March–May (MAM) and suppressed in September–November (SON). Meanwhile, a 30–50-day ISO of precipitation correlates with the SST over the Region A. SST leads precipitation by 10 days, implying a pronounced ocean–atmosphere interaction at the intraseasonal timescale, especially the oceanic feedback to the atmosphere during Madden–Julian Oscillation (MJO) events. Analysis on mechanism of the ISO manifests heat fluxes are critical to the development of the intraseasonal SST variability. The local thermocline in Region A, as the shallowest in MAM and the thickest in SON, is likely to modulate the strength of ISO and contribute to its sustainability. It suggests that thermocline plays a more important role in Region A than in Region B, leading to the difference between the two regions. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessCommunication
MJO Modulating the Activity of the Leading Mode of Intraseasonal Variability in South America
Atmosphere 2017, 8(12), 232; https://doi.org/10.3390/atmos8120232 - 28 Nov 2017
Cited by 6
Abstract
Intraseasonal (IS) variability in South America is efficiently described through the first empirical orthogonal function of filtered precipitation or outgoing longwave radiation (OLR) anomalies. In the 30–90-day band, the leading OLR pattern between October and April is a dipole with centers of action [...] Read more.
Intraseasonal (IS) variability in South America is efficiently described through the first empirical orthogonal function of filtered precipitation or outgoing longwave radiation (OLR) anomalies. In the 30–90-day band, the leading OLR pattern between October and April is a dipole with centers of action in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA). The Madden Julian Oscillation (MJO) was shown to have an impact on the rainfall in South America, with greater influence during the austral warm season. The aim of this study is therefore to assess the modulation of the MJO in the activity of the leading pattern of variability in South America, named the 3090-Seasonal-Intraseasonal (SIS) pattern. It was found that the most intense periods of activity of the SIS pattern appear to be related to intense MJO events with coherent eastward propagation. Furthermore, positive 3090-SIS phases, associated with enhanced (inhibited) convection over the SESA (SACZ) region generally occur during MJO progression from the eastern Indian Ocean to the Western Pacific (i.e., Maritime Continent sector). On the contrary, negative 3090-SIS phases, associated with enhanced (inhibited) convection over SACZ (SESA) are observed when the MJO active phase locates between the Western Pacific and the western Indian Ocean (African sector). The 3090-SIS pattern modulation by the MJO opens the opportunity to develop skillful subseasonal prediction tools in South America. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
Effect of Spatial Variation of Convective Adjustment Time on the Madden–Julian Oscillation: A Theoretical Model Analysis
Atmosphere 2017, 8(10), 204; https://doi.org/10.3390/atmos8100204 - 20 Oct 2017
Cited by 3
Abstract
The observed convective adjustment time (CAT) associated with Madden–Julian Oscillation (MJO) precipitation is found to vary significantly in space. Here, we investigate the effect of different spatial distributions of CAT on MJO precipitation based on the frictional coupled dynamics moisture (FCDM) model. The [...] Read more.
The observed convective adjustment time (CAT) associated with Madden–Julian Oscillation (MJO) precipitation is found to vary significantly in space. Here, we investigate the effect of different spatial distributions of CAT on MJO precipitation based on the frictional coupled dynamics moisture (FCDM) model. The results show that a large value of CAT tends to decrease the frequency and growth rate of eastward-propagating MJO-like mode in the FCDM model, delaying the occurrence of MJO deep convection and slowing down its eastward propagation. A large phase lag between circulation and convection decreases convective available potential energy (CAPE). In the observations, a small background vertical moisture gradient (BVMG) tends to increase the frequency associated with cold sea surface temperature (SST), while a large value of CAT tends to decrease the frequency. Due to their competing effect, the simulated frequency and phase speed remain the same when the convection moves from a warm to a cold SST region. The convection is heavily suppressed over the cold SST region due to the decreasing growth rate of unstable wavenumber-one mode with smaller BVMG and longer CAT. This theoretical finding should improve our understanding of MJO dynamics and simulation. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
Impact of Madden–Julian Oscillation upon Winter Extreme Rainfall in Southern China: Observations and Predictability in CFSv2
Atmosphere 2017, 8(10), 192; https://doi.org/10.3390/atmos8100192 - 30 Sep 2017
Cited by 8
Abstract
The impact of Madden–Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function (PDF) of November–March rainfall in southern China was found to [...] Read more.
The impact of Madden–Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function (PDF) of November–March rainfall in southern China was found to be skewed toward larger (smaller) values in phases 2–3 (6–7) of MJO, during which the probability of extreme rainfall events increased (reduced) by 30–50% (20–40%) relative to all days in the same season. Physical analysis indicated that the favorable conditions for generating extreme rainfall are associated with southwesterly moisture convergence and vertical moisture advection over southern China, while the direct contributions from horizontal moisture advection are insignificant. Based on the above results, the model-based predictability for extreme rainfall in winter was examined using hindcasts from the Climate Forecast System version 2 (CFSv2) of NOAA. It is shown that the modulations of MJO on extreme rainfall are captured and forecasted well by CFSv2, despite the existence of a relatively small bias. This study suggests the feasibility of deriving probabilistic forecasts of extreme rainfall in southern China based on RMM indices. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
Empirical Subseasonal Prediction of Summer Rainfall Anomalies over the Middle and Lower Reaches of the Yangtze River Basin Based on Atmospheric Intraseasonal Oscillation
Atmosphere 2017, 8(10), 185; https://doi.org/10.3390/atmos8100185 - 22 Sep 2017
Cited by 3
Abstract
The middle and lower reaches of the Yangtze River basin (MLRYB) are prone to flooding because their orientation is parallel to the East Asian summer monsoon rain belt. Since the East Asian summer monsoon presents pronounced intraseasonal variability, the subseasonal prediction of summer [...] Read more.
The middle and lower reaches of the Yangtze River basin (MLRYB) are prone to flooding because their orientation is parallel to the East Asian summer monsoon rain belt. Since the East Asian summer monsoon presents pronounced intraseasonal variability, the subseasonal prediction of summer precipitation anomalies in the MLRYB region is an imperative demand nationwide. Based on rotated empirical orthogonal function analysis, 48 stations over the MLRYB with coherent intraseasonal (10–80-day) rainfall variability are identified. Power spectrum analysis of the MLRYB rainfall index, defined as the 48-station-averaged intraseasonal rainfall anomaly, presents two dominant modes with periods of 20–30 days and 40–60 days, respectively. Therefore, the intraseasonal (10–80-day) rainfall variability is divided into 10–30-day and 30–80-day components, and their predictability sources are detected separately. Spatial-temporal projection models (STPM) are then conducted using these predictability sources. The forecast skill during the period 2003–2010 indicates that the STPM is able to capture the 30–80-day rainfall anomalies 5–30 days in advance, but unable to reproduce the 10–30-day rainfall anomalies over MLRYB. The year-to-year fluctuation in forecast skill might be related to the tropical Pacific sea surface temperature anomalies. High forecasting skill tends to appear after a strong El Niño or strong La Niña when the summer seasonal mean rainfall over the MLRYB is enhanced, whereas low skill is apparent after neutral conditions or a weak La Niña when the MLRYB summer seasonal mean rainfall is weakened. Given the feasibility of STPM, the application of this technique is recommended in the real-time operational forecasting of MLRYB rainfall anomalies during the summer flooding season. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
The Madden-Julian Oscillation: A Tool for Regional Seasonal Precipitation Outlooks?
Atmosphere 2017, 8(9), 180; https://doi.org/10.3390/atmos8090180 - 20 Sep 2017
Cited by 2
Abstract
The Madden-Julian Oscillation (MJO) is an important intraseasonal climate signal which circles the global tropics, but also impacts extratropical weather regimes. Few studies have investigated whether the MJO is a source of regional seasonal climate predictability. The present objective is to determine the [...] Read more.
The Madden-Julian Oscillation (MJO) is an important intraseasonal climate signal which circles the global tropics, but also impacts extratropical weather regimes. Few studies have investigated whether the MJO is a source of regional seasonal climate predictability. The present objective is to determine the extent to which the season and phase (geographic location) of MJO contribute to the frequency of global rainfall anomalies in ensuing seasons. Indices of June-July-August and December-January-February MJO activity for each phase and the El Niño/Southern Oscillation (ENSO) were correlated to three-month averages of rainfall up to a six-month lead time. Field significance was calculated and patterns of the relationships were described. In general, MJO shows some skill in regional seasonal precipitation prediction, but to a lesser extent than ENSO. However, the presence of MJO in the western Indian Ocean and near the date line did reveal a persistent and significant relationship with regional seasonal rainfall, especially over Northern Hemisphere land areas. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
Remote Ocean Response to the Madden–Julian Oscillation during the DYNAMO Field Campaign: Impact on Somali Current System and the Seychelles–Chagos Thermocline Ridge
Atmosphere 2017, 8(9), 171; https://doi.org/10.3390/atmos8090171 - 13 Sep 2017
Cited by 3
Abstract
During the CINDY/DYNAMO field campaign, exceptionally large upper ocean responses to strong westerly wind events associated with the Madden–Julian oscillation (MJO) were observed in the central equatorial Indian Ocean. Strong eastward equatorial currents in the upper ocean lasted more than one month from [...] Read more.
During the CINDY/DYNAMO field campaign, exceptionally large upper ocean responses to strong westerly wind events associated with the Madden–Julian oscillation (MJO) were observed in the central equatorial Indian Ocean. Strong eastward equatorial currents in the upper ocean lasted more than one month from late November 2011 to early January 2012. The remote ocean response to these unique MJO events are investigated using a high resolution (1/25°) global ocean general circulation model along with the satellite altimeter data. The local ocean response to the MJO events are realistically simulated by the global model based on the comparison with the data collected during the field campaign. The satellite altimeter data show that anomalous sea surface height (SSH) associated with the strong eastward jets propagated eastward as an equatorial Kelvin wave. The positive SSH anomalies then partly propagate westward as a reflected Rossby wave. The SSH anomalies associated with the reflected Rossby wave in the southern hemisphere propagate all the way to the western boundary. These remote ocean responses are well simulated by the global model. The analysis of the model simulation indicates the significant influence of reflected Rossby waves on sub-seasonal variability of Somali current system near the equator. The analysis further suggests that the reflected Rossby wave causes a substantial change in the structure of the Seychelles–Chagos thermocline ridge, which contributes to significant SST anomalies. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
Origins of Moist Air in Global Lagrangian Simulations of the Madden–Julian Oscillation
Atmosphere 2017, 8(9), 158; https://doi.org/10.3390/atmos8090158 - 26 Aug 2017
Cited by 4
Abstract
Many recent studies have characterized the Madden–Julian Oscillation (MJO) as a moisture mode, suggesting that its amplification and eastward propagation result from processes that build up moisture to the east of the MJO’s convective center, including frictionally driven boundary layer convergence, surface fluxes, [...] Read more.
Many recent studies have characterized the Madden–Julian Oscillation (MJO) as a moisture mode, suggesting that its amplification and eastward propagation result from processes that build up moisture to the east of the MJO’s convective center, including frictionally driven boundary layer convergence, surface fluxes, and shallow convection. Discussions of MJO moistening under this theory often implicitly assume an Eulerian framework; i.e., that local increases in moisture result from physical processes acting in the same location as the moistening is observed. In this study, the authors examine MJO moistening in a Lagrangian framework using a model that simulates atmospheric circulations by predicting the motions of individual air parcels. Back trajectories are presented for parcels in moist convecting regions of the MJO, and the effects of different physical processes on their moisture and moist static energy budgets are quantified. The Lagrangian MJO simulations suggest that much of the low-level moist air in heavily precipitating regions of the MJO arrives via the mid troposphere, coming from nearby equatorial regions, where it has been moistened largely by convective processes. Consequently, a thorough understanding of MJO moistening requires knowledge of the origin of the moist air and information about remote moisture sources. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle
An Alternative Estimate of Potential Predictability on the Madden–Julian Oscillation Phase Space Using S2S Models
Atmosphere 2017, 8(8), 150; https://doi.org/10.3390/atmos8080150 - 15 Aug 2017
Cited by 1
Abstract
This study proposes an alternative method to estimate the potential predictability without assuming the perfect model. A theoretical consideration relates a maximum possible value of the initial-value error to the covariance between analysis and bias-corrected ensemble-mean forecast. To test the method, the prediction [...] Read more.
This study proposes an alternative method to estimate the potential predictability without assuming the perfect model. A theoretical consideration relates a maximum possible value of the initial-value error to the covariance between analysis and bias-corrected ensemble-mean forecast. To test the method, the prediction limit of the Madden–Julian Oscillation (MJO) was evaluated, based on three pairs of reanalysis and forecast datasets provided by the European Centre for Medium-Range Weather Forecasting, the Japan Meteorological Agency and the National Centers for Environmental Prediction, participating in the subseasonal-to-seasonal prediction project. The results showed that the predictability was higher when MJO amplitude exceeded unity, consistent with the conventional method in which the error is evaluated as the ensemble-forecast spread. Moreover, the multimodel analysis was also conducted because the proposed method is readily applicable to the multimodel average of ensemble-mean forecasts. The phase dependency of the MJO’s potential predictability is also discussed. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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