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Jun Qin, Ailin Shi, Guoyu Ren, Zhenghong Chen, Yuda Yang, Xukai Zou, and Panfeng Zhang

Abstract

The White Crane Ridge (WCR) Rock Fish, now submerged under the backwater of the Three Gorges Reservoir in the Yangtze River, are affirmed as one of the earliest hydrologic observations ever made in any large river in the world. The usually in-water monument provides highly valuable historical records of severe droughts in the upper Yangtze over the last 1,200 years. This article updated the historical drought chronology previously developed based on the WCR inscriptions, which can be applied in assessment of extreme climatic and hydrological risks, and also made a preliminary analysis of changes of the severe drought frequency during the last thousand years in the upper Yangtze. The analysis shows that the severe droughts occurred more frequently during the Medieval Climate Anomaly (MCA), relatively less so during the Little Ice Age (LIA), and once again more often under the background of modern global warming. It was suggested that a generally warmer Euro-Asian continent during the MCA was in favor of the stronger East Asian summer monsoon, and the resulting less precipitation and more severe droughts of the Yangtze and the lower water level at the Three Gorges area on the centennial scale, and vice versa for the period of the LIA. The results would help in understanding the causes and mechanisms of the regional climate change and variability, and also in taking measures in the fields of the watershed management to cope with the long-term change in climatic and hydrologic droughts.

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Fan Yang, Qing He, Jianping Huang, Mamtimin Ali, Xinghua Yang, Wen Huo, Chenglong Zhou, Xinchun Liu, Wenshou Wei, Caixia Cui, Minzhong Wang, Hongjun Li, Lianmei Yang, Hongsheng Zhang, Yuzhi Liu, Xinqian Zheng, Honglin Pan, Lili Jin, Han Zou, Libo Zhou, Yongqiang Liu, Jiantao Zhang, Lu Meng, Yu Wang, Xiaolin Qin, Yongjun Yao, Houyong Liu, Fumin Xue, and Wei Zheng

CAPSULE

The Desert Environment and Climate Observation Network (DECON) could promote collaborative research on desert dust-storms, boundary-layer and land-atmosphere interactions to better understand the status and role of the Taklimakan desert.

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Ben P. Kirtman, Dughong Min, Johnna M. Infanti, James L. Kinter III, Daniel A. Paolino, Qin Zhang, Huug van den Dool, Suranjana Saha, Malaquias Pena Mendez, Emily Becker, Peitao Peng, Patrick Tripp, Jin Huang, David G. DeWitt, Michael K. Tippett, Anthony G. Barnston, Shuhua Li, Anthony Rosati, Siegfried D. Schubert, Michele Rienecker, Max Suarez, Zhao E. Li, Jelena Marshak, Young-Kwon Lim, Joseph Tribbia, Kathleen Pegion, William J. Merryfield, Bertrand Denis, and Eric F. Wood

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users.

The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model.

Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2011), a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data are readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (www.cpc.ncep.noaa.gov/products/NMME/). Moreover, the NMME forecast is already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, and presents an overview of the multimodel forecast quality and the complementary skill associated with individual models.

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