Prediction and attribution of quiescent tropical cyclone activity in the early summer of 2016: case study of lingering effects by preceding strong El Niño events

Takaya, Yuhei; Kubo, Yutaro; Maeda, Shuhei; Hirahara, Shoji

doi:10.1002/asl.760

Cited by 15 publications

(6 citation statements)

References 28 publications

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“…To obtain the model climatology, we also performed 10‐member hindcasts starting from the same calendar date during 1981–2010 with a compatible setting to that of EXP_CTRL. The second experiment (EXP_IOCLM) differs from EXP_CTRL in the treatment of SST conditions, as SSTs in the tropical IO were strongly constrained to the model climatology of the hindcast by applying a Newtonian nudging with a coefficient of 2,400 W m −2 K −1 , as described in a previous study (Takaya et al, 2017; Figure S2).…”

Section: Methodsmentioning

confidence: 99%

Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event

Takaya

Ishikawa

Kobayashi

et al. 2020

Geophysical Research Letters

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148

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In early summer 2020, the Meiyu-Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu-Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu-Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO-western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu-Baiu rainfall in 2020 originated from the super IOD. Plain Language Summary In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu-Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder-than-normal and warmer-than-normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation.

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Section: Methodsmentioning

confidence: 99%

Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event

Takaya

Ishikawa

Kobayashi

et al. 2020

Geophysical Research Letters

Self Cite

148

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“…This damping effect is strongest in regions where the ocean mixed layer is shallow (Mogensen et al, ). On the other hand, air–sea interactions in remote regions can change the large‐scale atmospheric environment in the TC development region through teleconnections (e.g., Wu et al, ; Takaya et al, ). This effect, which has been demonstrated in longer forecasts, could also alter shorter‐scale TC predictions for both location and intensity.…”

Section: Introductionmentioning

confidence: 99%

The effect of atmosphere–ocean coupling on the prediction of 2016 western North Pacific tropical cyclones

Feng

Klingaman

Hodges

2019

Quart J Royal Meteoro Soc

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We examine the merit of atmosphere-ocean coupled models for tropical cyclone (TC) predictions in the western North Pacific (WNP), where accurate TC predictions remain challenging. The UK Met Office operational atmospheric global numerical weather prediction (NWP) model is compared with two trial coupled configurations, in which the operational atmospheric model is coupled to a one-dimensional mixed-layer ocean model and a three-dimensional dynamical ocean model. Reforecasts for the 2016 TC season show that the coupled models outperform the NWP model for TC location predictions, with a systematic improvement of 50-100 km over the seven-day forecasts, but the coupled models amplify the underestimation of TC intensity in the NWP model. Nearly identical TC predictions (for both location and intensity) are found in the two coupled models, indicating the dominance of thermodynamic processes at the air-sea interface for TC predictions on these timescales. The improved prediction of the TC position in the coupled models is associated with an enhanced Western North Pacific Subtropical High (WNPSH), which introduces an anticyclonic steering flow anomaly that shifts TC tracks further west in the southern part of the region and further east in the northern part. Based on sensitivity experiments, we show that these improvements in the coupled models are due mainly to colder initial sea-surface temperatures (SSTs). Air-sea feedbacks do not change the WNPSH or TC tracks noticeably. Apart from the effect of the initial SSTs, tropical ocean warming due to air-sea interaction in the coupled forecasts can also reduce the predicted TC intensity, presumably due to a stronger regional Hadley circulation with increased subtropical subsidence.

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“…It has been revealed that the warmed tropical IO can account for as much as 50 % of the variance in the decrease of TC frequencies over the NWP during summer after the peak El Niño season (Du et al 2011;Zhan et al 2011, Kosaka et al 2013. Those observational studies were confirmed by sensitivity experiments using the air-sea coupled model (Takaya et al 2017), implicating the development of seasonal TC predictions.…”

Section: Introductionmentioning

confidence: 91%

Seasonal Modulation of Tropical Cyclone Occurrence Associated with Coherent Indo-Pacific Variability during Decaying Phase of El Niño

Ueda

Miwa

Kamae

2018

Journal of the Meteorological Society of Japan

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In this paper, the response of tropical cyclone (TC) activity to El Niño-Southern Oscillation (ENSO) and coherent sea surface temperature anomaly (SSTA) in the Indian Ocean (IO) is investigated, with a particular focus on the decaying phase of El Niño. The TC anomalies are obtained from the database for Policy Decision making for Future climate change (d4PDF). This dataset is based on 100-member ensemble simulations for the period of 1951-2010 using the state-of-the-art atmospheric general circulation model (AGCM) forced with the observed SST as well as the historical radiative forcing. The AGCM utilized in the d4PDF is the Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM) with about 60 km horizontal resolution. Our analysis revealed a prolonged decrease in TC frequency (TCF) over the tropical Western Pacific during the post-El Niño years until the boreal fall. Dominance of anomalous anticyclone (AAC) over the Western Pacific induced by the delayed warming in the tropical IO is the main factor for the suppressed TC activity rather than the local SST change. In contrast, the TC number over the South China Sea tends to increase during the post-El Niño fall (September to November). The physical reason can be ascribed to the weakening of the AAC associated with the termination of IO warming. Thus, we demonstrate that the effect of the IO warming should be taken into account when the ENSO is considered as an environmental factor for predicting TC activity.

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Prediction and attribution of quiescent tropical cyclone activity in the early summer of 2016: case study of lingering effects by preceding strong El Niño events

Cited by 15 publications

References 28 publications

Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event

Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event

The effect of atmosphere–ocean coupling on the prediction of 2016 western North Pacific tropical cyclones

Seasonal Modulation of Tropical Cyclone Occurrence Associated with Coherent Indo-Pacific Variability during Decaying Phase of El Niño

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