MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model

Wu, Jie; Ren, Hong‐Li; Zuo, Jinqing; Zhao, Chunmei; Chen, Lijuan; Li, Qiaoping

doi:10.1016/j.dynatmoce.2016.06.001

Cited by 45 publications

(44 citation statements)

References 48 publications

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“…As PWV variability in the Chajnantor region is related to atmospheric circulation and Rossby wave activity (Falvey and Garreaud, ), linking PWV to the MJO may extend PWV predictability and be useful to operational scheduling at the site, particularly given that forecasts of PWV from the Global Forecast System (GFS) model drop below skill (correlation) of 0.7 after about 120 h (Sarazin et al ., ). The MJO has shown statistically significant predictability in global NWP models well beyond 120 h. For example, prediction skill of the RMM indices of approximately 21 days (Kim et al ., ) was found in the Climate Forecast System version 2 (CFSv2), of 3–4 weeks (Xiang et al ., ) in the Geophysical Fluid Dynamics Laboratory (GFDL) model, of 27 days (Miyakawa et al ., ) in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), and of 16–17 days (Wu et al ., ) in an ensemble of the Beijing Climate Center Atmospheric General Circulation Model. All of these studies suggest that the tropical MJO can act as an effective bridge into subseasonal prediction of extratropical atmospheric events (Jones, ), including PWV amounts in the Chajnantor region.…”

Section: Methodsmentioning

confidence: 99%

Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile

Marı́n

Barrett

2017

Intl Journal of Climatology

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The Chajnantor plateau is located in the Atacama Desert at over 4800 m above sea level. The plateau features a large fraction of days during the year where dry and stable atmospheric conditions predominate. The suitability of the type of astronomy observations routinely made at sites across the Chajnantor region at different times of the year depends on the variability of atmospheric water vapour. In this work, we study seasonal and intraseasonal variability associated with periods of large and low precipitable water vapour (PWV) in the Chajnantor region over 32 years. We establish large‐scale conditions favourable for above‐ and below‐normal PWV for each of the four seasons. We also explore whether intraseasonal PWV variations are related to the Madden–Julian Oscillation (MJO). Below‐normal PWV in winter, spring, and autumn seasons was found associated with mostly zonal 500‐hPa winds, which advect drier than normal air from the anticyclone over the eastern portions of the southeast (SE) Pacific Ocean. In summer, periods with below‐normal PWV were found to have anomalously south‐westerly winds at mid‐levels, also indicating transport of anomalously dry air from the stable SE Pacific. In winter, spring, and autumn seasons, above‐normal PWV was generally associated with north‐westerly mid‐tropospheric wind anomalies, indicating advection of above‐normal PWV from the subtropical and tropical regions of the SE Pacific Ocean. Above‐normal PWV conditions in summer were associated with nearly calm winds at 500 hPa. Months and phases of the MJO for the most extreme anomalies of PWV for each season agreed well with the seasonal anomalies. Furthermore, three independent reanalysis data sets generally agreed on MJO phases associated with largest positive and negative PWV anomalies. This agreement provides evidence for the first time that the MJO modulates the PWV content over the Atacama Desert.

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Section: Methodsmentioning

confidence: 99%

Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile

Marı́n

Barrett

2017

Intl Journal of Climatology

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“…Recent notable studies of the influence of tropical‐extratropical interactions on forecast skill have used reforecasts made with full GCMs (see Hamill & Kiladis, ; Scaife et al, ; Vitart & Molteni, ; Vitart, ; Wu et al, for recent examples) and re‐forecasts made with statistical models, in particular the Linear Inverse Model (LIM), (e.g., Newman et al, ; Pegion & Sardeshmukh, ; Winkler et al, ). Vitart and Molteni () targeted the response of the extratropics to the MJO‐related tropical diabatic heating in ECMWF forecasts out to 15 days and find that the response in the North Atlantic bears the same time‐lagged relationship to the MJO as found by Cassou () and Lin et al (): positive NAO phase is preferentially excited about 10 days after the MJO heating is in the Indian Ocean (phase 3 of the MJO), while the MJO heating in the western Pacific (phase 6) is correlated with the appearance of the negative NAO phase 10 days later.…”

Section: Forecasting Tropical‐extratropical Interactionsmentioning

confidence: 99%

Review of Tropical‐Extratropical Teleconnections on Intraseasonal Time Scales

Stan

Straus

Frederiksen

et al. 2017

Reviews of Geophysics

259

214

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The interactions and teleconnections between the tropical and midlatitude regions on intraseasonal time scales are an important modulator of tropical and extratropical circulation anomalies and their associated weather patterns. These interactions arise due to the impact of the tropics on the extratropics, the impact of the midlatitudes on the tropics, and two‐way interactions between the regions. Observational evidence, as well as theoretical studies with models of complexity ranging from the linear barotropic framework to intricate Earth system models, suggest the involvement of a myriad of processes and mechanisms in generating and maintaining these interconnections. At this stage, our understanding of these teleconnections is primarily a collection of concepts; a comprehensive theoretical framework has yet to be established. These intraseasonal teleconnections are increasingly recognized as an untapped source of potential subseasonal predictability. However, the complexity and diversity of mechanisms associated with these teleconnections, along with the lack of a conceptual framework to relate them, prevent this potential predictability from being translated into realized forecast skill. This review synthesizes our progress in understanding the observed characteristics of intraseasonal tropical‐extratropical interactions and their associated mechanisms, identifies the significant gaps in this understanding, and recommends new research endeavors to address the remaining challenges.

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“…MJO prediction skill is also suggested to be dependent on its initial and target amplitudes, with higher skills for the strong cases than the weak ones (Lin et al, 2008;Rashid et al, 2011;Xiang et al, 2015;Wu, Ren, Zuo, et al, 2016). Here, we emphasize that the improvement of prediction skill is more apparent for the initially weak cases than for the strong cases ( Figure 3a).…”

Section: Journal Of Geophysical Research: Atmospheresmentioning

confidence: 70%

“…On the other hand, better ocean initial conditions also advance the MJO prediction skill in the operational dynamical model (Fu et al, 2013;Liu et al, 2017). Essentially, the moisture initialization was included in some dynamic subseasonal to seasonal (S2S) prediction models (Fu et al, 2013;Vitart, 2014;Wang et al, 2014) but was not included in others, such as Geophysical Fluid Dynamics Laboratory (GFDL) coupled model (Xiang et al, 2015), the BCC S2S operational model (Liu et al, 2017;Wu, Ren, Zuo, et al, 2016), and the regional simulation study conducted by Weather Research and Forecasting model . Therefore, a realistic initial moisture condition could be crucial for MJO prediction , which is also well-known sensitive to the convective parameterization in dynamical models (Klingaman & Woolnough, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a realistic initial moisture condition could be crucial for MJO prediction , which is also well-known sensitive to the convective parameterization in dynamical models (Klingaman & Woolnough, 2014). Essentially, the moisture initialization was included in some dynamic subseasonal to seasonal (S2S) prediction models (Fu et al, 2013;Vitart, 2014;Wang et al, 2014) but was not included in others, such as Geophysical Fluid Dynamics Laboratory (GFDL) coupled model (Xiang et al, 2015), the BCC S2S operational model (Liu et al, 2017;Wu, Ren, Zuo, et al, 2016), and the regional simulation study conducted by Weather Research and Forecasting model . However, the benefits of the inclusion of moisture initialization have not been fully understood, and fewer studies have compared the MJO prediction with or without moisture initialization in addition to the commonly used dynamic nudging scheme.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effects of Moisture Initialization on MJO and its Teleconnection Prediction in BCC Subseasonal Coupled Model

Ren

Lü

et al. 2020

JGR Atmospheres

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It is well recognized that moisture is of great importance in the representation of the Madden-Julian Oscillation (MJO). In this study, a moisture initialization scheme is developed using the Beijing Climate Center (BCC) subseasonal operational coupled model, and its effects on MJO predictions are investigated. Three sets of hindcast experiments are conducted: a reference experiment without moisture initialization (REF) and two sensitivity experiments with moderate and strong moisture nudging schemes. We show that the prediction skill of the real-time multivariate MJO index is significantly improved in the two sensitivity experiments, where the skillful prediction can reach up to 20 days using the moderate nudging scheme. Larger improvements can be achieved when MJO was initiated from Phases 2-3 and 5-7 or during La Niña episodes, implying that the MJO prediction skill is more sensitive to moisture conditions in active convection regions and backgrounds. The moisture budget analysis indicated that the MJO prediction improvement using the moisture initialization schemes comes from the realistic representation of vertical moisture structure and vertical moisture advection to the east of the MJO convection in the planetary boundary layer. The improved MJO prediction is also demonstrated to enable a more reliable subseasonal prediction of extratropical circulation and precipitation through a more realistic description of MJO-related teleconnections. In addition, the ensemble mean of the three schemes can extend the MJO prediction skill to more than 22 days, showing the potential benefits of ensemble prediction of multiinitialization schemes.

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MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model

Cited by 45 publications

References 48 publications

Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile

Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile

Review of Tropical‐Extratropical Teleconnections on Intraseasonal Time Scales

Effects of Moisture Initialization on MJO and its Teleconnection Prediction in BCC Subseasonal Coupled Model

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