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Bin Wang and Zhen Fan

In the south Asian region, two of the major precipitation maxima associated with areas of intensive convective activity are located near the Bay of Bengal and in the vicinity of the Philippines. The variations of monthly mean outgoing longwave radiation in the two regions are poorly correlated, particularly in the decade of 1980s. The enhanced convection over the Bay of Bengal and Indian subcontinents is coupled with reinforced monsoon circulation west of 80°E over India, the western Indian Ocean, and the tropical northern Africa. In contrast, the enhanced convection in the vicinity of the Philippines corresponds to intensified monsoon circulation primarily east of 80°E over southeast Asia including the Indochina peninsula, South China Sea, Philippine Sea, and the Maritime Continent. To better reflect regional monsoon characteristics, two convection indices (or associated circulation indices that are dynamically coherent with the convection indices) are suggested to measure the variability of the Indian summer monsoon (ISM) and the southeast Asian summer monsoon, respectively.

The change in the Bay of Bengal convection (the ISM) has planetary-scale implications, whereas the change in Philippine convection has primarily a regional impact including a linkage with the east Asia subtropical monsoon. The equatorial western Pacific winds exhibit a considerably higher correlation with the ISM convection than with the Philippine convection. During the summers when a major Pacific warm episode occurs (e.g., 1982–83, 1986–87, 1991–92, and 1997), the convection and circulation indices describing the ISM often diverge considerably, causing inconsistency among various normally coherent monsoon indices. This poses a primary difficulty for using a single monsoon index to characterize the interannual variability of a regional monsoon. The cause of the breakdown of the coherence between various convection and circulation indices during ENSO warm phase needs to be understood.

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Tim Li, Lu Wang, Melinda Peng, Bin Wang, Chidong Zhang, William Lau, and Hung-Chi Kuo

Abstract

The Madden–Julian oscillation (MJO) identified by Madden and Julian in the early 1970s has been well recognized as the most prominent intraseasonal signal in the tropics. Its discovery and its relationship with other weather phenomena such as tropical cyclones (TCs) are among the most significant advancements in modern meteorology with broad and far-reaching impacts. The original study by Madden and Julian used radiosonde data on Canton Island, and their spectral analysis revealed the signal of a 40–50-day oscillation.

It has come to our attention that an earlier study by Xie et al. published in a Chinese journal documented an oscillatory signal of a 45-day period using radiosonde data from several stations between 70° and 125°E in the tropics. The 40–50-day signal found by Xie et al. is strikingly evident without any filtering. Xie et al. identified that occurrences of TCs are correlated with the 40–50-day variation of low-level westerlies at these stations. The original figures in Xie et al.’s article were hand drawn. Their results are verified using data from a longer period of 1958–70. The 40–50-day oscillation in the monsoon westerlies and its relationship with the occurrence of TCs are confirmed and further expanded upon.

This study serves the purpose of bringing recognition to the community of the identification of a 40–50-day signal published in Chinese in 1963 and the discovery of the correlation between MJO phases and TC genesis three decades earlier than studies on this subject published outside China.

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Hao He, Hailong Wang, Zhaoyong Guan, Haishan Chen, Qiang Fu, Muyin Wang, Xiquan Dong, Chunguang Cui, Likun Wang, Bin Wang, Gang Chen, Zhanqing Li, and Da-Lin Zhang
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Jinyoung Rhee, Wenju Cai, Neil Plummer, Mannava Sivakumar, Nina Horstmann, Bin Wang, and Dewi Kirono
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Yanluan Lin, Yuanlong Li, Qingshan Li, Minyan Chen, Fanghua Xu, Yuqing Wang, and Bin Huang
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Chih-Pei Chang, Richard H. Johnson, Kyung-Ja Ha, Daehyun Kim, Gabriel Ngar-Cheung Lau, Bin Wang, Michael M. Bell, and Yali Luo
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Yali Luo, Renhe Zhang, Qilin Wan, Bin Wang, Wai Kin Wong, Zhiqun Hu, Ben Jong-Dao Jou, Yanluan Lin, Richard H. Johnson, Chih-Pei Chang, Yuejian Zhu, Xubin Zhang, Hui Wang, Rudi Xia, Juhui Ma, Da-Lin Zhang, Mei Gao, Yijun Zhang, Xi Liu, Yangruixue Chen, Huijun Huang, Xinghua Bao, Zheng Ruan, Zhehu Cui, Zhiyong Meng, Jiaxiang Sun, Mengwen Wu, Hongyan Wang, Xindong Peng, Weimiao Qian, Kun Zhao, and Yanjiao Xiao

Abstract

During the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.

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Bin Wang, Michela Biasutti, Michael P. Byrne, Christopher Castro, Chih-Pei Chang, Kerry Cook, Rong Fu, Alice M. Grimm, Kyung-Ja Ha, Harry Hendon, Akio Kitoh, R. Krishnan, June-Yi Lee, Jianping Li, Jian Liu, Aurel Moise, Salvatore Pascale, M. K. Roxy, Anji Seth, Chung-Hsiung Sui, Andrew Turner, Song Yang, Kyung-Sook Yun, Lixia Zhang, and Tianjun Zhou

Abstract

Monsoon rainfall has profound economic and societal impacts for more than two-thirds of the global population. Here we provide a review on past monsoon changes and their primary drivers, the projected future changes, and key physical processes, and discuss challenges of the present and future modeling and outlooks. Continued global warming and urbanization over the past century has already caused a significant rise in the intensity and frequency of extreme rainfall events in all monsoon regions (high confidence). Observed changes in the mean monsoon rainfall vary by region with significant decadal variations. Northern Hemisphere land monsoon rainfall as a whole declined from 1950 to 1980 and rebounded after the 1980s, due to the competing influences of internal climate variability and radiative forcing from greenhouse gases and aerosol forcing (high confidence); however, it remains a challenge to quantify their relative contributions. The CMIP6 models simulate better global monsoon intensity and precipitation over CMIP5 models, but common biases and large intermodal spreads persist. Nevertheless, there is high confidence that the frequency and intensity of monsoon extreme rainfall events will increase, alongside an increasing risk of drought over some regions. Also, land monsoon rainfall will increase in South Asia and East Asia (high confidence) and northern Africa (medium confidence), decrease in North America, and be unchanged in the Southern Hemisphere. Over the Asian–Australian monsoon region, the rainfall variability is projected to increase on daily to decadal scales. The rainy season will likely be lengthened in the Northern Hemisphere due to late retreat (especially over East Asia), but shortened in the Southern Hemisphere due to delayed onset.

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Stephen Baxter, Gerald D Bell, Eric S Blake, Francis G Bringas, Suzana J Camargo, Lin Chen, Caio A. S Coelho, Ricardo Domingues, Stanley B Goldenberg, Gustavo Goni, Nicolas Fauchereau, Michael S Halpert, Qiong He, Philip J Klotzbach, John A Knaff, Michelle L'Heureux, Chris W Landsea, I.-I Lin, Andrew M Lorrey, Jing-Jia Luo, Andrew D Magee, Richard J Pasch, Petra R Pearce, Alexandre B Pezza, Matthew Rosencrans, Blair C Trewin, Ryan E Truchelut, Bin Wang, H Wang, Kimberly M Wood, and John-Mark Woolley
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Sid A. Boukabara, Tong Zhu, Hendrik L. Tolman, Steve Lord, Steven Goodman, Robert Atlas, Mitch Goldberg, Thomas Auligne, Bradley Pierce, Lidia Cucurull, Milija Zupanski, Man Zhang, Isaac Moradi, Jason Otkin, David Santek, Brett Hoover, Zhaoxia Pu, Xiwu Zhan, Christopher Hain, Eugenia Kalnay, Daisuke Hotta, Scott Nolin, Eric Bayler, Avichal Mehra, Sean P. F. Casey, Daniel Lindsey, Louie Grasso, V. Krishna Kumar, Alfred Powell, Jianjun Xu, Thomas Greenwald, Joe Zajic, Jun Li, Jinliong Li, Bin Li, Jicheng Liu, Li Fang, Pei Wang, and Tse-Chun Chen

Abstract

In 2011, the National Oceanic and Atmospheric Administration (NOAA) began a cooperative initiative with the academic community to help address a vexing issue that has long been known as a disconnection between the operational and research realms for weather forecasting and data assimilation. The issue is the gap, more exotically referred to as the “valley of death,” between efforts within the broader research community and NOAA’s activities, which are heavily driven by operational constraints. With the stated goals of leveraging research community efforts to benefit NOAA’s mission and offering a path to operations for the latest research activities that support the NOAA mission, satellite data assimilation in particular, this initiative aims to enhance the linkage between NOAA’s operational systems and the research efforts. A critical component is the establishment of an efficient operations-to-research (O2R) environment on the Supercomputer for Satellite Simulations and Data Assimilation Studies (S4). This O2R environment is critical for successful research-to-operations (R2O) transitions because it allows rigorous tracking, implementation, and merging of any changes necessary (to operational software codes, scripts, libraries, etc.) to achieve the scientific enhancement. So far, the S4 O2R environment, with close to 4,700 computing cores (60 TFLOPs) and 1,700-TB disk storage capacity, has been a great success and consequently was recently expanded to significantly increase its computing capacity. The objective of this article is to highlight some of the major achievements and benefits of this O2R approach and some lessons learned, with the ultimate goal of inspiring other O2R/R2O initiatives in other areas and for other applications.

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