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Ángel F. Adames and Yi Ming

GFDL’s atmospheric general circulation model (AM4.0). They found a strong coupling between anomalous precipitation and column moisture. By jointly analyzing the moisture and moist static energy budgets, they found that the moisture anomalies propagate because of horizontal advection of mean dry static energy (DSE) by the anomalous winds. Horizontal advection of DSE induces a moisture tendency by forcing ascent along the sloping isentropes of the monsoon region. The anomalous precipitation is

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Enrique R. Vivoni, Kinwai Tai, and David J. Gochis

1. Introduction and background Soil moisture initialization in meteorological models can significantly affect the performance of weather forecasts (e.g., Mahfouf 1991 ; Beljaars et al. 1996 ; Schär et al. 1999 ; Koster et al. 2004a ). Since various studies have indicated a strong sensitivity of rainfall on soil moisture (e.g., Mintz 1984 ; Mo et al. 2006 ; Aligo et al. 2007 ), a proper initialization can potentially enhance precipitation predictability ( Miyakoda et al. 1979 ; Beljaars

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Tao Feng, Jia-Yuh Yu, Xiu-Qun Yang, and Ronghui Huang

) . Because moist deep convection is, to a great extent, controlled by the buildup and removal of tropospheric moisture ( Sherwood 1999 ; Raymond 2000 ; Bretherton et al. 2004 ; Holloway and Neelin 2009 ), the total precipitable water was also found to be phase locked with TD-type disturbances in Part I . The maximum total precipitable water appears near the center of the disturbances, while the maximum tendency of total precipitable water leads the cyclonic vortex at one-quarter wavelength. Such

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Ángel F. Adames and Daehyun Kim

phenomena that are affected by it. However, in order to improve MJO simulation, a better understanding of the fundamental processes driving its dynamics is required. There is a growing body of theoretical work in which the MJO is considered to be a “moisture mode” ( Neelin and Yu 1994 ; Raymond 2000b , 2001 ; Sobel et al. 2001 ; Sobel and Gildor 2003 ; Fuchs and Raymond 2002 , 2005 , 2007 ; Sugiyama 2009a , b ; Majda and Stechmann 2009 ; Sobel and Maloney 2012 , 2013 , hereafter SM refers

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Randal D. Koster, Rolf H. Reichle, and Sarith P. P. Mahanama

1. Introduction The Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010 ) mission provides estimates, across the globe, of moisture in the top several centimeters of soil at a spatial resolution of about 40 km and with a revisit time of 3 days or less. To promote the use of the data in the community, the data are produced with a mean latency of 24 h, close to real time for many applications. We posit, as motivation for the present paper, that some users of these data may find utility in

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Lan Dai, Jonathon S. Wright, and Rong Fu

anomalies requires detailed diagnosis of the moisture budget and its relationships to changes in the energy budget and large-scale circulation ( Seager and Henderson 2013 ). Moisture budget analysis, which relates regional precipitation and evaporation to moisture flux convergence, has been demonstrated to be useful in determining the causes of extreme hydroclimatic events, as precipitation anomalies are directly affected by changes in moisture sources and transport ( Seager et al. 2010 ). Further

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Yeonjoo Kim and Guiling Wang

1. Introduction Many climatologists have speculated on the role of soil moisture in the midlatitude climate. Namias (1952) hypothesized that soil moisture could support month-to-month persistence in climatic anomalies over the United States. This hypothesis has been followed by numerous studies on land–atmosphere interactions, focusing on soil moisture–precipitation feedback. Precipitation influences soil moisture; the resulting anomalies in soil moisture feed back to impact precipitation

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Ángel F. Adames and Yi Ming

the best of our knowledge, the first study to examine the water vapor budget of SMDs was Yoon and Chen (2005) . They found that the leading balance in SMDs involves import of moisture through convergence and loss of moisture through condensation and precipitation. Their study, however, only considered the Eulerian temporal tendency in moisture over a limited domain near the center of the vortex. Thus, their study does not take into account the propagation of the moisture anomalies. However

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Max C. A. Torbenson and David W. Stahle

1. Introduction Monthly time scale persistence of drought and wetness can play an important role in the forecasting of seasonal moisture levels ( Preisler and Westerling 2007 ; Mason and Baddour 2008 ; Hao et al. 2014 ). Spring moisture conditions in the central United States have some skill in predicting the baseline probability of summer drought ( Lyon et al. 2012 ; Otkin et al. 2015 ). A nationwide perspective on the correlation between spring soil moisture and the atmospheric moisture

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Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson

moisture, fraction of green vegetation cover (  f c ), and leaf area index (LAI; Wetzel and Chang 1987 ; van den Hurk et al. 1997 ; Crawford et al. 2001 ; Kurkowski et al. 2003 ; Richter et al. 2004 ). These variables are not readily or easily observed on the scales needed to initialize NWP models, and therefore such models often rely on parameterized routines to provide a representation of the current land surface state. Soil moisture is an especially difficult LSM state variable because

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