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Haishan Chen, Bo Yu, Botao Zhou, Wanxin Zhang, and Jie Zhang

radiation effects and the feedback of land–atmosphere interaction on the warm amplification over arid/semiarid regions. In addition, various studies have explored the possible reasons for the abnormal warming of the Eurasian continent from aspects of changes in cloud amount ( Dai et al. 1997 , 1999 ; Tang and Leng 2012 ; Tang et al. 2012 ) and precipitation ( Dai et al. 1997 , 1999 ; Trenberth and Shea 2005 ). Dai et al. (1997 , 1999) pointed out that increased cloud amount can reduce solar

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Joseph A. Santanello Jr., Christa D. Peters-Lidard, and Sujay V. Kumar

1. Introduction The inherent coupled nature of earth’s energy and water cycles places significant importance on the proper representation and diagnosis of land–atmosphere (LA) interactions in hydrometeorological prediction models ( Entekhabi et al. 1999 ; Betts and Silva Dias 2010 ). Unfortunately, the disparate resolutions and complexities of the governing processes have made it difficult to quantify these interactions in models or observations ( Angevine 1999 ; Betts 2000 ; Cheng and

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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

surface states on global climate have relied on parameterizations of the land surface coupled to weather and climate models. This modeling approach is used to understand large-scale patterns and long-term statistics (cf. Seneviratne et al. 2010 ). The Coupled Model Intercomparison Project phase 5 (CMIP5; Taylor et al. 2012 ) provides an opportunity for multimodel assessment of the evolving nature of land–atmosphere interactions from past to present to future. A much broader evaluation is possible

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Joshua K. Roundy and Eric F. Wood

interactions ( Koster et al. 2000 ). There has been a great deal of work over the last decade to quantify land–atmosphere interactions and feedbacks over a variety of scales that utilize observations and prediction models. Working groups as part of the Global Energy and Water Cycle Experiment (GEWEX) initiative have done much of this work. One such effort focuses on the local land–atmosphere coupling through diagnosing the interactions between the land surface and the planetary boundary layer for models

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Shanshui Yuan, Steven M. Quiring, and Chen Zhao

inhibition; enhancing the probability of convective precipitation over drier soils ( Ford et al. 2015a , 2018 ; Tuttle and Salvucci 2016 ). Hence, soil moisture is a critical variable for both characterizing drought conditions and for investigating land–atmosphere interactions. Drought indices have been used to characterize near-surface moisture conditions in some land–atmosphere interaction studies because of the lack of available soil moisture measurements. For example, Hirschi et al. (2010) used

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Zhong Zhong, Yuan Sun, Xiu-Qun Yang, Weidong Guo, and Haishan Chen

describe the exchange of water, heat, and momentum across the land–atmosphere interface ( Brutsaert 1998 ; Albertson and Parlange 1999 ). Substantial progresses in representing the role of surface heterogeneity on land–atmosphere interaction has been achieved ( Henderson-Sellers and Pitman 1992 ; Lyons and Halldin 2004 ; Kanda et al. 2007 ; Ma et al. 2008 ; Brunsell et al. 2011 ). Numerous efforts have attempted to address the land surface parameters, such as roughness length, to ascertain area

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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

vary from year to year ( Guo and Dirmeyer 2013 ) depending on the pattern of the climatology of soil moisture and the fluctuation of its anomalies. These results raise questions. Have the interactions between land and atmosphere on intraseasonal to interannual time scales changed since preindustrial times when atmospheric composition, aerosol loading, and global vegetation cover were different? More importantly, will land–atmosphere interactions change in the future? Phase 5 of the Coupled Model

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Jessica M. Erlingis and Ana P. Barros

1. Introduction Previously, the southern Great Plains (SGP) region was identified as a maximum “hot spot” for land–atmosphere interactions on time and spatial scales relevant for climate studies ( Koster et al. 2004 ), though the coupling mechanism proper, in particular the seasonality and spatial scales of soil moisture S and precipitation P feedbacks (e.g., the S – P relationship) and the role of evapotranspiration, remains the subject of active research ( Luo et al. 2007 ; Wei et al

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L. R. Vargas Zeppetello, Étienne Tétreault-Pinard, D. S. Battisti, and M. B. Baker

shown in Figs. 2 and 3 are due to errors in the model representations of the connection between surface turbulent energy fluxes and soil moisture. In this paper, we take a first step toward addressing this hypothesis with the aid of our “toy model” of land–atmosphere interaction on monthly time scales, developed in sections 2 and 3 . For more details on model development, see Tétreault-Pinard (2013) . The model quantitatively links the variance in 2-m air temperature T and soil moisture m

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Anna M. Wilson and Ana P. Barros

orographic land–atmosphere interactions associated with the observed diurnal cycle of warm rainfall in the SAM, including reverse orographic enhancement and cloud immersion. WB15 showed that patterns of moisture convergence in weak and strong synoptic forcing conditions modified by the terrain result in “hot spots” consistent with LLCF formation patterns that support seeder–feeder interactions with propagating precipitation systems as proposed by WB14 . From observations ( WB14 ; WB15 ), a synthesis

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