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Christopher P. Weaver

1. Introduction Land–atmosphere interactions are an important part of the hydrologic cycle and climate. A growing body of evidence suggests that land surface variables can have a significant impact on the atmosphere, from the scales of individual thunderstorms up to globally [see Pielke (2001) for a review]. A significant effort is underway to improve seasonal-to-interannual prediction using information about soil moisture, snow cover, and vegetation, since more accurate descriptions of land

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Eli J. Dennis and Ernesto Hugo Berbery

1. Introduction It has long been understood that the land surface is a critical component of the climate system and that soil moisture is a key factor for determining land surface–atmosphere interactions and coupling ( Sellers et al. 1996 ; Koster et al. 2004 ; Seneviratne et al. 2010 ). The strength of the coupling between soil moisture and other variables depends on the time scale, ranging from daily-to-weekly time scales ( Santanello et al. 2011 ; Tawfik and Dirmeyer 2014 ) to monthly

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Daniel E. Comarazamy, Jorge E. González, Jeffrey C. Luvall, Douglas L. Rickman, and Pedro J. Mulero

-scale trade wind advection, coastal tropical cities will not be affected by drought-inducing higher cloud bases due to changes in the Bowen ratio over land. However, this hypothesis remains inconclusive, and we believe it underestimates the complexity of the competing multiscale factors involved in these land–ocean–atmosphere interactions. Thus, a number of research questions arise regarding the understanding of these and other competing effects due to LCLU changes in tropical coastal regions. These

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Ana Paula Barros

2144 JOURNAL OF CLIMATE VOLUME8Adaptive Multilevel Modeling of Land-Atmosphere Interactions ANA PAULA BARROSDepartment of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pennsylvania(Manuscript received 20 July 1994, in final form 7 March 1995) Adaptive multilevel methods allow full coupling of atmospheric and land

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Christopher P. Weaver

1. Introduction The goal of this two-part study is to investigate general questions relating to mesoscale land–atmosphere interactions in the summertime in the U.S. Southern Great Plains (SGP) region. Specifically, how do the synoptic-scale shifts in background meteorology modulate these diurnal, mesoscale land–atmosphere interaction processes, and how important might these mesoscale processes be to the overall large-scale hydrometeorology? Part I ( Weaver 2004 ) focused on case studies drawn

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Michael Notaro, Guangshan Chen, Yan Yu, Fuyao Wang, and Ahmed Tawfik

climate model (RCM), with accurate representation of vegetation characteristics, may be needed to accurately study land–atmosphere interactions over such geographically and ecologically complex regions. Few studies have examined the influence of intraseasonal-to-interannual LAI variations on regional climate, despite its potential importance to short-term climate prediction. Modeling studies by Xue et al. (2010) and Notaro et al. (2011a) suggested that the global monsoon regions respond uniquely

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Yan Yu, Michael Notaro, Fuyao Wang, Jiafu Mao, Xiaoying Shi, and Yaxing Wei

simulated land–atmosphere interactions ( Koster et al. 2006 , 2010 ; Liu et al. 2006 ; Notaro et al. 2011 , 2017 ), and few studies have attempted to validate simulated vegetation feedbacks against observations to give credibility to their findings ( Notaro and Liu 2008 ; Wang et al. 2013 , 2014 ). Indeed, land–atmosphere interactions remain a key source of uncertainty in climate modeling and climate change projections ( Flato et al. 2013 ). Given the substantial uncertainties in the sign and

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Zhenzhong Zeng, Shilong Piao, Laurent Z. X. Li, Tao Wang, Philippe Ciais, Xu Lian, Yuting Yang, Jiafu Mao, Xiaoying Shi, and Ranga B. Myneni

indicated that Earth greening has contributed to the increasing trend in global land ET over the last 30 years. However, the offline algorithm used to separate the contributions of each of the drivers in their studies cannot isolate the interactions among the drivers. In the observations, none of the driving factors can be considered in isolation given their strong interactions with each other. For example, an increase of P is likely to increase ET, but the increase of P itself could also be a

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Paola A. Arias, J. Alejandro Martínez, Juan David Mejía, María José Pazos, Jhan Carlo Espinoza, and Sly Wongchuig-Correa

relationship between SSTs in the Atlantic, and moisture recycling and enhanced NDVI over the northern Orinoco. The causality of this relationship needs to be further explored. In particular, we require further research to understand the land–atmosphere interactions in the Orinoco basin, for instance the role of surface energy fluxes and their influence on cloudiness and fire activity in surrounding regions. Our results suggest elements that link changes in surface temperatures in the tropical Atlantic

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Xiaoyan Jiang, Sara A. Rauscher, Todd D. Ringler, David M. Lawrence, A. Park Williams, Craig D. Allen, Allison L. Steiner, D. Michael Cai, and Nate G. McDowell

projected vegetation, and climate characteristics from the ensemble simulations. Finally, discussion and conclusions are presented in section 4 . 2. Methods a. Model description The model utilized here is the atmosphere and land components of the global CESM, which was previously known as the Community Climate System Model (CCSM). To allow for interactions between climate and vegetation, the model was run in a configuration in which the atmosphere model (Community Atmosphere Model) and CLM4.0 are

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