Distinct impacts of the MJO and the NAO on cold wave amplitude in China

Lyu, Mengxia; Wu, Zhiwei; Shi, Xiaohui; Wen, Min

doi:10.1002/qj.3516

Cited by 10 publications

(4 citation statements)

References 67 publications

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“…Meanwhile, an anomalous upper-tropospheric ridge moves eastward from eastern Europe and intensifies over the Ural Mountains (Figures 3A1-D1). The above results are analogous to the impact of a decaying NAO event on the Ural ridge and the East Asian winter circulation mentioned by previous studies (Luo et al, 2010;Sung et al, 2011;Wang et al, 2011;Song and Wu, 2017;Lyu et al, 2019).…”

Section: Climatology Of the Cold Surgesupporting

confidence: 90%

Distinct Mid-Latitude Eurasian Rossby Wave Trains Preceding Strong and Weak Cold Surges in Southern China

Lin

Cheung

2022

Front. Earth Sci.

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This study investigates the large-scale circulation anomalies of strong and weak cold surges in southern China. Results show that the strong and weak surges are associated with a distinct Rossby wave train across Eurasia projecting onto the Scandinavia (SCAND) and Eurasian (EU) patterns. On one hand, the strong surge is preceded by a positive SCAND pattern and a transition of the EU pattern from its negative to positive phase. The corresponding wave train propagates southeastward from East Asia to the North Pacific. This is associated with a strong intensification of the Siberian high, a deepened East Asian trough, and a sharp meridional pressure gradient between northern and southern China; these advect intense cold air masses from Siberia to southern China. On the other hand, the weak surge is preceded by a negative SCAND pattern and a positive EU pattern. The corresponding wave train does not propagate from East Asia to the North Pacific. This wave train has a weak impact on the East Asian winter monsoon circulation and corresponds to weak cold air advections towards southern China. Overall, the intra-seasonal variation of the Eurasian teleconnection patterns is crucial for a comprehensive understanding of the cold surge in southern China.

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Section: Climatology Of the Cold Surgesupporting

confidence: 90%

Distinct Mid-Latitude Eurasian Rossby Wave Trains Preceding Strong and Weak Cold Surges in Southern China

Lin

Cheung

2022

Front. Earth Sci.

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“…In addition to the BSISO, the MJO is also one of the targets for improving the S2S forecast in this study, given that the MJO is a dominant mode of intraseasonal atmospheric variability and exerts remarkable modulations on the tropical and extra-tropical weather and climate events (e.g., Kikuchi and Wang 2010;He et al 2011;Moon et al 2013;Hsu et al 2016;Lyu et al 2019b). Liu et al (2017) showed that the useful skill of MJO forecast by the BCC model was about 16 days in the S2S hindcasts, and increased to 18 days by optimizing atmospheric initial conditions and 22 days by optimizing both atmospheric and oceanic initial conditions.…”

Section: Discussionmentioning

confidence: 99%

Impacts of atmospheric and oceanic initial conditions on boreal summer intraseasonal oscillation forecast in the BCC model

Liu

et al. 2020

Theor Appl Climatol

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In this paper, we evaluate the capability of the Beijing Climate Center Climate System Model (BCC-CSM) in simulating and forecasting the boreal summer intraseasonal oscillation (BSISO), using its simulation and sub-seasonal to seasonal (S2S) hindcast results. Results show that the model can generally simulate the spatial structure of the BSISO, but give relatively weaker strength, shorter period, and faster transition of BSISO phases when compared with the observations. This partially limits the model’s capability in forecasting the BSISO, with a useful skill of only 9 days. Two sets of hindcast experiments with improved atmospheric and atmosphere/ocean initial conditions (referred to as EXP1 and EXP2, respectively) are conducted to improve the BSISO forecast. The BSISO forecast skill is increased by 2 days with the optimization of atmospheric initial conditions only (EXP1), and is further increased by 1 day with the optimization of both atmospheric and oceanic initial conditions (EXP2). These changes lead to a final skill of 12 days, which is comparable to the skills of most models participated in the S2S Prediction Project. In EXP1 and EXP2, the BSISO forecast skills are improved for most initial phases, especially phases 1 and 2, denoting a better description for BSISO propagation from the tropical Indian Ocean to the western North Pacific. However, the skill is considerably low and insensitive to initial conditions for initial phase 6 and target phase 3, corresponding to the BSISO convection’s active-to-break transition over the western North Pacific and BSISO convection’s break-to-active transition over the tropical Indian Ocean and Maritime Continent. This prediction barrier also exists in many forecast models of the S2S Prediction Project. Our hindcast experiments with different initial conditions indicate that the remarkable model errors over the Maritime Continent and subtropical western North Pacific may largely account for the prediction barrier.

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“…For example, the mean state exerts a strong control on MJO propagation characteristics (Jiang et al, 2020). The MJO may also play an active role in shaping the midlatitude mean state winds, for example through the modulation of the local Hadley cell (Lyu et al, 2019). Such feedbacks are not simulated in the LBM.…”

Section: Discussionmentioning

confidence: 99%

Mechanisms driving MJO teleconnection changes with warming in CMIP6

Jenney¹,

Randall²,

Barnes³

2021

Preprint

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Abstract. Teleconnections from the Madden-Julian Oscillation (MJO) are a key source of predictability of weather on the extended time scale of about 10–40 days. The MJO teleconnection is sensitive to a number of factors, including the mean state dry static stability, the mean flow, and the propagation and intensity characteristics of the MJO itself, which are traditionally difficult to separate across models. Each of these factors may evolve in response to increasing greenhouse gas emissions, which will impact MJO teleconnections and potentially impact potential predictability on extended time scales. Current state-of-the-art climate models do not agree on how MJO teleconnections will change in a future climate. Here, we use results from the Coupled Model Intercomparison Project Phase 6 (CMIP6) historical and SSP585 experiments in concert with a linear baroclinic model to separate and investigate alternate mechanisms explaining why and how MJO teleconnections over the North Pacific and North America will change in a future climate, and to identify key sources of inter-model uncertainty. We find that decreases to the MJO teleconnection due to increases in tropical dry static stability alone are robust, and that uncertainty in mean state winds are a key driver of uncertainty in future MJO teleconnections. We find no systematic relationship between changes in Rossby wave excitation and the MJO teleconnection. However, we find that models that predict increases (decreases) in the stationary Rossby wave number over the gulf of Alaska also predict stronger (weaker) teleconnections over North America. Uncertainty in future changes to the MJO's intensity, eastward propagation speed, and eastward propagation extent are other important sources of uncertainty in future MJO teleconnections, although to a lesser degree than uncertainty in the mean state. The overall outlook is a reduction of the boreal winter MJO teleconnection across the vast majority of CMIP6 models, especially over the North Pacific, but with some nuance over North America due to larger sensitivity to expansion of the MJO's eastward extent.

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Distinct impacts of the MJO and the NAO on cold wave amplitude in China

Cited by 10 publications

References 67 publications

Distinct Mid-Latitude Eurasian Rossby Wave Trains Preceding Strong and Weak Cold Surges in Southern China

Distinct Mid-Latitude Eurasian Rossby Wave Trains Preceding Strong and Weak Cold Surges in Southern China

Impacts of atmospheric and oceanic initial conditions on boreal summer intraseasonal oscillation forecast in the BCC model

Mechanisms driving MJO teleconnection changes with warming in CMIP6

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