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Omar V. Müller, Pier Luigi Vidale, Benoît Vannière, Reinhard Schiemann, Retish Senan, Reindert J. Haarsma, and Johann H. Jungclaus

overlying atmosphere. In these areas, soil moisture modulates land–atmosphere feedbacks through the exchanges of latent and sensible heat fluxes ( Koster et al. 2004 ). It also interacts and modifies runoff, regulating changes in river flows. Through these processes, the state of the land–atmosphere coupling can modify the persistence and intensity of droughts or wet spells ( Seneviratne et al. 2006 ). Given the critical role of land–atmosphere interactions in the climate system, some community

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Volker Wulfmeyer, David D. Turner, B. Baker, R. Banta, A. Behrendt, T. Bonin, W. A. Brewer, M. Buban, A. Choukulkar, E. Dumas, R. M. Hardesty, T. Heus, J. Ingwersen, D. Lange, T. R. Lee, S. Metzendorf, S. K. Muppa, T. Meyers, R. Newsom, M. Osman, S. Raasch, J. Santanello, C. Senff, F. Späth, T. Wagner, and T. Weckwerth

A novel synergy of scanning lidar systems as well as other in situ and remote sensing instruments provides accurate 3D measurements of numerous dynamical and thermodynamical quantities to evaluate and improve our understanding of land–atmosphere interactions. The L–A system includes the soil, the land cover such as vegetation, and the overlying atmo-sphere (see the appendix for a list of key acronyms used in this paper). The interaction of variables (e.g., related to the water and energy

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Joseph A. Santanello Jr., Joshua Roundy, and Paul A. Dirmeyer

1. Introduction Land–atmosphere (L–A) interactions and coupling remain weak links in current approaches to understanding and improving predictions of the Earth–atmosphere system and its variability in a changing climate. However, recent community-based efforts (e.g., LandFlux; Mueller et al. 2013 ) have shown that current observational and model products have significant uncertainty and spread in surface [e.g., evapotranspiration (ET)] and planetary boundary layer (PBL) water and energy budget

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Seungbum Hong, Venkat Lakshmi, and Eric E. Small

. 2001 , Weiss et al. 2004 ). Various studies have dealt with these interactions, including the development of land–atmosphere models ( Noilhan and Planton 1989 ; Pitman 1991 ; Xue et al. 1991 ) and the relation of vegetation dynamics to other land and climate variables ( Betts et al. 1997 ; Bounoua et al. 1999 ; Weiss et al. 2004 ). Meteorological and climatological conditions both impact and are influenced by vegetation distribution and dynamics ( Sellers et al. 1996 ; Betts et al. 1997

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Tomoko Nitta, Kei Yoshimura, and Ayako Abe-Ouchi

1. Introduction Land areas exhibit complex processes in the cryosphere, hydrosphere, and the land surface itself, which all interact with the climate system through complex interactions and feedbacks ( Seneviratne et al. 2010 ). Understanding the land–atmosphere coupling strength, the degree to which anomalies in the land surface can affect atmospheric processes, is important because this coupling modulates the climate system and, hence, is a key element of climate models ( Koster et al. 2006

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Katherine Dagon and Daniel P. Schrag

changes due to SRM and do not explore changes in land–atmosphere water cycling in detail. Some studies consider vegetation–climate feedbacks and plant physiology ( Fyfe et al. 2013 ; Irvine et al. 2014 ; Glienke et al. 2015 ) but not soil moisture and runoff. Of particular importance are how those factors are parameterized, how well constrained are the parameterizations in terms of observations, and how variations within reasonable ranges of plausible parameterizations will affect the results. In

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G. Louis Smith and David A. Rutan

uniquely suited for study of the diurnal cycle of OLR. Daily variability of OLR results from interactions of the surface and atmosphere due to temperature, cloud, and humidity variations during the day. These daily variations may be divided into diurnal variations, which repeat periodically, and transient variations due to weather events, which do not repeat on a daily cycle. Accurate knowledge of the diurnal cycle is crucial for several reasons. For sun-synchronous satellites, knowledge of the diurnal

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Bradley G. Illston, Jeffrey B. Basara, Christopher A. Fiebrich, Kenneth C. Crawford, Eric Hunt, Daniel K. Fisher, Ronald Elliott, and Karen Humes

1. Introduction Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Anomalous soil moisture conditions on a large scale can lead to droughts or floods ( Delworth and Manabe 1989 , 1993 ), while regional variations can impact the development of the planetary boundary layer ( Zdunkowski et al. 1975 ; Betts and Ball 1995 ), the formation of low-level boundaries or land breezes ( Enger and Tjernstrom 1991 ; Segal and Arritt 1992 ), convective initiation

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G. Balsamo, J-F. Mahfouf, S. Bélair, and G. Deblonde

subgrid information is considered. 3. The land surface scheme The land surface processes are represented by the Interaction Soil Biosphere Atmosphere (ISBA) scheme that has been described in detail by Noilhan and Planton (1989) , Noilhan and Mahfouf (1996) , and Bélair et al. (2003a , b ). The operational version of ISBA at MSC considers the evolution of six prognostic variables for soil and vegetation: T s is the surface temperature, T p is the daily mean surface temperature, w s is the

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Lucas R. Vargas Zeppetello, David S. Battisti, and Marcia B. Baker

due to the complexity of land–atmosphere interaction no singular cause has been identified. However, model representations of evaporation have been implicated as a primary cause of temperature biases in climate models ( Mueller and Seneviratne 2014 ; Merrifield and Xie 2016 ; Ma et al. 2018 ). Variations in evaporation are linked to variations in soil moisture, which has become widely regarded as a fundamental control on summertime temperatures ( Seneviratne et al. 2010 ). While current

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