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Kevin Schwarzwald, Andrew Poppick, Maria Rugenstein, Jonah Bloch-Johnson, Jiali Wang, David McInerney, and Elisabeth J. Moyer

descending regions, He and Li (2018) posit that moisture availability is too low for these changes to matter, so that precipitation variability should rise as the mean. The drivers of the apparent increases seen in model studies remain an open question. In this work, we seek to extend on previous studies by conducting self-consistent or near-consistent studies of precipitation changes across a wider range of spatial and temporal scales: from 3-hourly to decadal in time scale and from 12 km to global in

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Claude Frankignoul, Guillaume Gastineau, and Young-Oh Kwon

temperature in the first decade of the twenty-first century. The pause in surface warming has been largely attributed to natural variability in the tropical Pacific Ocean (e.g., Meehl et al. 2013 ; Kosaka and Xie 2013 ; Trenberth et al. 2014 ; England et al. 2014 ), perhaps in part driven by Atlantic changes ( McGregor et al. 2014 ; Chen and Tung 2014 ; Li et al. 2015 ; Ruprich-Robert et al. 2017 ). However, a recent SST bias correction suggests that there was no global warming slowdown ( Karl et

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Xidong Wang, Chunzai Wang, Liping Zhang, and Xin Wang

) examined the interdecadal variability of the summertime typhoon tracks over the WNP. They divided the 1951–2001 periods into two subperiods of 1951–79 and 1980–2001 and found that the typhoon passage frequency decreased significantly over the East China Sea and the Philippine Sea, but increased slightly over the South China Sea in the latter period. Examining various thermodynamic and dynamic factors, Chan (2008) found that the frequency and tracks of category 4 and 5 TCs in the WNP undergo decadal

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Jing-Jia Luo, Sebastien Masson, Swadhin K. Behera, and Toshio Yamagata

-like variability (e.g., Ji et al. 1996 ; Luo and Yamagata 2001 ). Interannual ENSO events over the past two decades are predicted with high skill scores up to 12 months in advance (see Luo et al. 2005b ). Some strong ENSO events are even predictable about 1½ yr ahead ( Fig. 3 , black lines). The El Niño condition in the 1997/98 winter can be predicted to some extent at about a 1½-yr lead with the forecasted amplitude reaching the 0.5°C criterion for El Niño definition (see the yellow lines in Fig. 4d

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Justin A. Schulte, Nickitas Georgas, Vincent Saba, and Penelope Howell

1. Introduction It has been identified that modes of climate variability impact coastal water temperature variability. The impact of North Pacific sea surface temperature (SST) patterns such as the Pacific decadal oscillation (PDO; Mantua et al. 1997 ) and North Pacific Gyre Oscillation (NPGO; Di Lorenzo et al. 2008 ) on coastal water temperature variability across the U.S. West Coast is well established ( Cloern et al. 2010 ). However, the influence of the PDO on eastern U.S. coastal waters

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Christine T. Y. Chung, Scott B. Power, Agus Santoso, and Guomin Wang

1. Introduction Multiyear to decadal variability is evident in rainfall, temperature, severe weather, and flood frequency around the globe, including the Southern Hemisphere ( Power et al. 2017 , manuscript submitted to CLIVAR Exchanges ). This can cause hardship and loss of life (see, e.g., Power et al. 2005 ; Power and Callaghan 2016 ). It is therefore important that we understand the cause of this variability and the extent to which it can be predicted. While the warming trend in the

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Chuan-Yang Wang, Shang-Ping Xie, Yu Kosaka, Qinyu Liu, and Xiao-Tong Zheng

regression may help evaluate the performance of each model in POGA simulations with regard to decadal modulations of GMST changes. By separating internal variability into interannual and decadal components, we show that the impact of tropical Pacific SST on GMST is larger in magnitude on decadal time scales than on interannual time scales in a multimodel mean sense. This time-scale dependency has implications for observational estimates of the Pacific effect on GMST. The relatively short instrumental

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Alexandre O. Fierro and Lance M. Leslie

1. Introduction Climate variability over Australia is affected by several large-scale drivers, some with larger impacts than others over specific region(s) of the continent. In the last four decades, a plethora of studies have identified the following climate drivers as playing a key role on the global climate over Australia: the Antarctic Oscillation (AAO) or southern annular mode (SAM) ( Trenberth 1979 ; Rogers and van Loon 1982 ; Karoly 1990 ; Gong and Wang 1999 ; Thompson and Solomon

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Chunlüe Zhou and Kaicun Wang

associated with the warming trend ( Lenderink and Van Meijgaard 2008 ). Among these processes, upward vertical velocity may produce more precipitation extremes for interannual variations than for a warming trend ( Allen and Ingram 2002 ; O’Gorman and Schneider 2009b ). Generally, ENSO dominates the interannual climate variability over the tropics, and its low-frequency variability further extends the effect to decadal–multidecadal time scales and to the mid-to-high latitudes ( Trenberth et al. 1998

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Asher B. Siebert and M. Neil Ward

decadal to multidecadal variability (MDV) in a random stochastic sense, a feature sometimes not explicitly emphasized in GCM scenarios. In this paper, the methodology is applied to seasonal rainfall totals at four representative sites in Africa, and with a particular motivating problem of index insurance. The aim is to provide insights into the levels of bias and uncertainty in estimating event frequencies into the future, under specified assumptions of climate variability and change. The framework

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