El Niño–Southern Oscillation complexity

Timmermann, Axel; An, Soon Il; Kug, Jong‐Seong; Jin, Fei; Cai, Wenju; Capotondi, Antonietta; Cobb, Kim M.; Lengaigne, Matthieu; McPhaden, Michael J.; Stuecker, Malte F.; Stein, Karl; Wittenberg, Andrew T.; Yun, Kyung Sook; Bayr, Tobias; Chen, Han Ching; Chikamoto, Yoshimitsu; Dewitte, Boris; Dommenget, Dietmar; Grothe, Pamela R.; Guilyardi, Éric; Ham, Yoo‐Geun; Hayashi, Minoru; Ineson, Sarah; Kang, Daehyun; Kim, Sunyong; Kim, WonMoo; Lee, June‐Yi; Li, Tim; Luo, Jie; McGregor, Shayne; Planton, Yann; Power, Scott B.; Rashid, Harun; Ren, Hong Li; Santoso, Agus; Takahashi, K.; Todd, Alexander D.; Wang, Guomin; Wang, Guojian; Xie, Rui; Yang, Woo Hyun; Yeh, Sang‐Wook; Yoon, Jin‐Ho; Zeller, Elke; Zhang, Xuebin

doi:10.1038/s41586-018-0252-6

Cited by 783 publications

(678 citation statements)

References 95 publications

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“…Last but not least, the proposed ENSO‐HRB‐SCR teleconnection largely agrees with a recent finding, from which extreme rainfall days in the south and north China (separated by 30°N) were associated with the rapidly decaying El Niño and developing La Niña, respectively (Li & Wang, ). The teleconnection may be explained by the combination mode dynamics (Stuecker et al, , ; Timmermann et al, ). It illustrates that the transition from El Niño to La Niña in a near‐annual cycle suppresses the low‐level cyclonic activity over the central Pacific, and subsequently gives rise to an intensified WNPSH+.…”

Section: Discussionmentioning

confidence: 99%

Summer Monsoon Rainfall Patterns and Predictability over Southeast China

Dai

Cheng

2020

Water Resources Research

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This study advances the use of the Self‐organizing Map (SOM) to identify the summer monsoon rainfall patterns over Southeast China (SEC), using 272 gauge records from May to August. Three distinct rain belts over the Huai River basin (HRB), the Lower Yangtze River basin (LYRB) and the South Coast region (SCR) are found. Their subseasonal variability strongly agrees with the northward progression of the East Asian Summer Monsoon (EASM) front in a stepwise fashion. We find that precipitation in the SCR and HRB rain belts exhibit significant changes in the mid‐1990s, while the 1990s is the most active decade for the LYRB rain belt. Promising predictability of average daily rainfall over these three regions is obtained, with about 39% to 50% of the total variance explained by the circulation informed regression models. Both leave‐one‐year‐out cross‐validation and blind prediction verify the regression performance. The western North Pacific Subtropical High phases, mid‐latitude blocking high anomaly over northeast China and upper‐level divergence in SEC are found to best explain the variability of the rain belts. The newly proposed Russia‐China wave patterns (western/central Russia → north of Tibetan Plateau → SEC) and teleconnection between the El Niño‐Southern Oscillation and the rain belts also offer additional predictability. Findings from this work may advance the understanding of the EASM rain belts, and offer insights to the source of bias for numerical simulations of daily summer monsoon rainfall in the region.

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Section: Discussionmentioning

confidence: 99%

Summer Monsoon Rainfall Patterns and Predictability over Southeast China

Dai

Cheng

2020

Water Resources Research

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“…Year‐to‐year sea surface temperature (SST) variations in the equatorial oceans have tremendous climatic impacts on tropical countries (Birkett et al, ; Tierney et al, ; Thirumalai et al, ) as well as remote regions throughout the world (Klein et al, ; Timmermann et al, ). These fluctuations are large in the Pacific and Atlantic Oceans, where strong equatorial upwelling and a shallow thermocline in the east favor ocean‐atmosphere interactions giving rise to the El Niño–Southern Oscillation (ENSO) and the Atlantic Niño (Jin, ; Neelin et al, ; Zebiak, ).…”

Section: Introductionmentioning

confidence: 99%

An El Niño Mode in the Glacial Indian Ocean?

Thirumalai

DiNezio

Tierney

et al. 2019

Paleoceanog and Paleoclimatol

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Despite minor variations in sea surface temperature (SST) compared to other tropical regions, coupled ocean‐atmosphere dynamics in the Indian Ocean cause widespread drought, wildfires, and flooding. It is unclear whether changes in the Indian Ocean mean state can support stronger SST variability and climatic extremes. Here we focus on the Last Glacial Maximum (19,000–21,000 years before present) when background oceanic conditions could have been favorable for stronger variability. Using individual foraminiferal analyses and climate model simulations, we find that seasonal and interannual SST variations in the eastern equatorial Indian Ocean were much larger during this glacial period relative to modern conditions. The increase in year‐to‐year variance is consistent with the emergence of an equatorial mode of climate variability, which strongly resembles the Pacific El Niño and is currently not active in the Indian Ocean.

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“…An additional question is the origin of warm SST anomalies in the SCS. The El Niño–Southern Oscillation (ENSO) is a potential source as it is the largest mode of interannual climate variability in the region (Timmermann et al, ). Our results show that the ENSO index calculated from the data assimilation‐based reconstructed SSTs is significantly and negatively correlated to the data assimilation‐based reconstructed precipitation PC2 ( r = –0.57) and the proxy‐based reconstructed precipitation PC1 ( r = –0.50) shown in Figure S13.…”

Section: Resultsmentioning

confidence: 99%

Monopole Mode of Precipitation in East Asia Modulated by the South China Sea Over the Last Four Centuries

Shi

Goosse

Klein

et al. 2019

Geophysical Research Letters

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Precipitation in East Asia affects one quarter of the global population. However, the mechanisms governing precipitation changes at the century scale remain unclear. Reconstructions of warm season precipitation over the last 531 years show that the dominant mode of variability is a monopole covering most of China. However, this mode is mostly absent from Coupled Model Intercomparison Project Phase 5 results. In contrast, experiments using data assimilation reproduce this monopole mode well. Results show that sea surface temperature in the South China Sea is a major driver of the monopole mode of precipitation via a Gill-type response. Warm sea surface temperatures induce a distinct baroclinic structure over the central part of eastern China comprising a low-pressure cyclone in the lower troposphere and a high-pressure anticyclone in the upper troposphere with rising airflow, resulting in water vapor convergence and increased precipitation in East Asia.Plain Language Summary Precipitation in East Asia affects more than one billion people.Although recent changes in precipitation depend on latitude, reconstructions based on paleoclimate archives show that over the last four centuries, East Asia has been characterized by a spatially homogeneous change in precipitation. However, this feature is not present in current climate model simulations. Here, we reproduce this monopole pattern using a combination of model results and observational data using a data assimilation approach and identify the physical processes that lead to this pattern. The observed increase in precipitation over China is due to increased water transport and rising air in this region. These atmospheric circulation changes are linked to a heat source at the surface of the South China Sea caused by higher water temperatures. This work demonstrates that the dominant mode of precipitation variability in East Asia over the past four centuries may differ from the current mode. the annual mean (July-June) Niño 3.4 region SST anomalies and the data assimilation-based and proxybased reconstructed MJJAS precipitation indicates a weak north-south dipole ( Figure S18). ConclusionsThe dominant monopole mode of precipitation variability over the period 1470-1849 found in proxybased reconstructions in East Asia is reproduced by combining precipitation data and model results from CESM-LME applying a data assimilation technique based on a particle filter method. The EOF main loading of the monopole mode is located in the middle and lower reaches of the Yangtze and Yellow Rivers. This suggests that the monopole mode of the precipitation conforms to physical climate laws used by climate models. Based on an atmospheric circulation analysis, the monopole mode of MJJAS precipitation variability over East Asia is linked with warm SST anomalies in the SCS, which leads to a distinct baroclinic structure over the central part of eastern China via a Gill-type response. Correspondingly, local rising airflow, more water vapor convergence, a greater cloud fraction, and more prec...

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El Niño–Southern Oscillation complexity

Cited by 783 publications

References 95 publications

Summer Monsoon Rainfall Patterns and Predictability over Southeast China

Summer Monsoon Rainfall Patterns and Predictability over Southeast China

An El Niño Mode in the Glacial Indian Ocean?

Monopole Mode of Precipitation in East Asia Modulated by the South China Sea Over the Last Four Centuries

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