Pathways to Better Prediction of the MJO: 2. Impacts of Atmosphere‐Ocean Coupling on the Upper Ocean and MJO Propagation

Savarin, Ajda; Chen, Shuyi S.

doi:10.1029/2021ms002929

Cited by 9 publications

(14 citation statements)

References 79 publications

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“…4. The CTRL's precipitation signal is noisier than in observations due to its higher resolution and a high bias in precipitation (see Savarin and Chen (2022b), their AO4-FLX experiment). The post-MJO suppression in CTRL is not as strong as was observed, but it does propagate through the MC, even though the signal is not as smooth as over the IO or in observations (Fig.…”

Section: Mjo Characteristics In Model Simulationsmentioning

confidence: 99%

“…The atmosphere-ocean coupled model used in this study is the Unified Wave Interface -Coupled Model (UWIN-CM) (Chen et al, 2013;Chen & Curcic, 2016). All simulations use the configuration that was described in Savarin and Chen (2022b) which includes convection-permitting resolution, atmosphere-ocean coupling, and a modification to air-sea flux parameterization to yield a good simulation of the observed MJO event.…”

Section: Model Configuration and Simulationsmentioning

confidence: 99%

“…In the IMERG dataset, the November-December 2011 MJO event remains cohesive and propagates through the MC up to a precipitation threshold of 22 mm. When model simulations are compared to observations, a threshold of 17 mm is used instead of 12 mm to highlight differences between simulations, as the model tends to overproduce precipitation (see Savarin & Chen, 2022b). At lower thresholds, MJO propagation over the MC can be seen in LPT tracking, but it tends to present as a series of discrete longitude jumps, as the tracking algorithm attempts to connect distinct areas of precipitation with little overlap.…”

Section: Large-scale Precipitation Tracking Of the Mjomentioning

confidence: 99%

“…The datasets used in this study include the high-resolution global terrain model (ETOPO1; NOAA National Geophysical Data Center, 2009), the Global Precipitation Measurement's Integrated Multi-satellite Retrievals (IMERG; Huffman, Stocker, et al, 2019), and the Cross-calibrated Multi-platform gridded surface vector winds (CCMP; Wentz et al, 2015). UWIN-CM (the Unified Wave Interface -Coupled Model) was used to run the simulations, and is described in Section 2.1 as well as in previous studies such as Savarin and Chen (2022b). The modeling software is available upon request.…”

Section: Open Researchmentioning

confidence: 99%

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Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent

Savarin

Chen

2022

Preprint

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Large-scale convection associated with the Madden-Julian Oscillation (MJO) initiates over the Indian Ocean and propagates eastward across the Maritime Continent (MC). Over the MC, MJO events are generally weakened due to complex interactions between the large-scale MJO and the MC landmass. The MC barrier effect is responsible for the dissipation of 40-50\% of observed MJO events and is often exaggerated in weather and climate models. We examine how MJO propagation over the MC is affected by two aspects of the MC -its land-sea contrast and its terrain. To isolate the effects of mountains and landsea contrast on MJO propagation, we conduct three high-resolution coupled atmosphere-ocean model experiments: 1) control simulation (CTRL) of the 2011 November-December MJO event, 2) flattened terrain without MC mountains (FLAT), and 3) no-land simulation (WATER) in which the MC islands are replaced with 50 m deep ocean. CTRL captures the general properties of the diurnal cycle of precipitation and MJO propagation across the MC. The WATER simulation produces a more intense and smoother-propagating MJO compared with that of CTRL. In contrast, the FLAT simulation produces much more convection and precipitation over land (without mountains) than CTRL, which results in a stronger barrier effect on MJO propagation. The land-sea contrast induced land-locked convection weakens the MJO's convective organization. The land-locked convective systems over land in FLAT are more intense, grow larger, and last longer, which is more detrimental to MJO propagation over the MC, than the mountains that are present in CTRL.

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Section: Mjo Characteristics In Model Simulationsmentioning

confidence: 99%

Section: Model Configuration and Simulationsmentioning

confidence: 99%

Section: Large-scale Precipitation Tracking Of the Mjomentioning

confidence: 99%

Section: Open Researchmentioning

confidence: 99%

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Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent

Savarin

Chen

2022

Preprint

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“…AO4 simulations show a high precipitation bias, mostly in the suppressed regime after the MJO has passed out of the IO (Figure 5). The positive precipitation bias is a result of a high bias in air‐sea latent heat flux, which is addressed in a companion paper by Savarin and Chen (2022, part 2). None of the model simulations can reproduce the suppressed phase of the MJO to the extent that we see in observations (Figure 5).…”

Section: Discussionmentioning

confidence: 97%

Pathways to Better Prediction of the MJO: 1. Effects of Model Resolution and Moist Physics on Atmospheric Boundary Layer and Precipitation

Savarin

Chen

2022

J Adv Model Earth Syst

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The Madden-Julian Oscillation (MJO) is the leading source of tropical intraseasonal variability with a wide range of impacts on global weather and climate (Zhang, 2013). The MJO is characterized by an alternating large-scale pattern of active and suppressed precipitation with corresponding enhanced westerly and easterly zonal winds (Madden & Julian, 1971, 1972. Active convection associated with the MJO typically initiates over the Indian Ocean (IO), propagates eastward over the Maritime Continent (MC) and into the western Pacific before decaying. Within the large-scale MJO convective envelope, deep convection is predominately organized in mesoscale convective systems or cloud clusters (Chen et al., 1996;Takayabu, 1994;Zhang, 2005). The mesoscale convective systems can enhance surface westerly winds through the downward transport of momentum into the atmospheric boundary layer

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The effect of diurnal warming of sea‐surface temperatures on the propagation speed of the Madden–Julian oscillation

Karlowska,

Matthews,

Webber

et al. 2023

Quart J Royal Meteoro Soc

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The diurnal warm layer in the upper ocean develops during low surface winds and high incoming solar radiation conditions, often increasing sea surface temperatures (SSTs) by up to 1∘ C. The suppressed phase of the Madden–Julian Oscillation (MJO) favours the formation of such a layer. Here we analyse the coupled ocean–atmosphere and atmosphere‐only Numerical Weather Prediction systems of the UK Met Office to reveal that important differences arise from the representation of the diurnal warm layer in the coupled model. While both models are skilful in predicting the MJO to at least 7‐day lead time, the coupled model predicts approximately10% faster MJO propagation than the atmosphere‐only model due to the ability to resolve diurnal warming in the upper ocean that rectifies onto MJO‐associated SST anomalies. The diurnal warming of SST (dSST) in the coupled model leads to an increase in daily mean SST compared with the atmosphere‐only model persisted foundation SST. The strength of the dSST in the coupled model is modulated by MJO conditions. During suppressed MJO conditions on lead day 1, the dSST is enhanced leading to 0.2∘ C warmer daily mean MJO‐associated SST anomalies and increased convection in the coupled model by lead day 7. During active MJO convection, the dSST is suppressed, leading to 0.1∘ C colder MJO‐associated SST anomalies in the coupled model and reduced convection by lead day 7. This variability in dSST further amplifies the MJO propagation speed, underlining the importance of the two‐way feedback between the MJO and the diurnal cycle of SST and the need to accurately represent this process in coupled models.This article is protected by copyright. All rights reserved.

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Pathways to Better Prediction of the MJO: 2. Impacts of Atmosphere‐Ocean Coupling on the Upper Ocean and MJO Propagation

Cited by 9 publications

References 79 publications

Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent

Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent

Pathways to Better Prediction of the MJO: 1. Effects of Model Resolution and Moist Physics on Atmospheric Boundary Layer and Precipitation

The effect of diurnal warming of sea‐surface temperatures on the propagation speed of the Madden–Julian oscillation

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