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Paul A. Dirmeyer, C. Adam Schlosser, and Kaye L. Brubaker

predictions. We therefore hypothesize that not only are interactions between the land and atmosphere a considerable source of land surface memory but that this memory poses an element of coupled land–atmosphere predictability in the climate system that can advance water cycle prediction. In this paper, we bring together disparate methods and datasets to investigate evidence of land–atmosphere feedbacks. In so doing, we wish to avoid the possibility of a particular result being the artifact of a single

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Mauro Sulis, John L. Williams, Prabhakar Shrestha, Malte Diederich, Clemens Simmer, Stefan J. Kollet, and Reed M. Maxwell

al. 2011 ; Orth and Seneviratne 2012 ). The interaction between soil moisture and the atmosphere evolves through exchanges of energy, mass, and momentum at the land surface, which are in turn influenced by topography, soil properties, and vegetation characteristics ( Sellers et al. 1995 ; Pielke 2001 ; Teuling et al. 2006 , 2010 ; Los et al. 2006 ). Recently, studies suggested that groundwater may function as a spatial organizer of soil moisture by maintaining wetter conditions in low

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Lu Li, Wei Shangguan, Yi Deng, Jiafu Mao, JinJing Pan, Nan Wei, Hua Yuan, Shupeng Zhang, Yonggen Zhang, and Yongjiu Dai

feedback was strong on dry days but had less impact on wet days. It is known that P on wet days in the southeastern United States is generally caused by cyclones, mesoscale convective systems, and even large-scale weather systems ( Henderson and Robinson 1994 ; Silvestri and Vera 2003 ; Bombardi et al. 2014 ), rather than by local land–atmosphere interactions. However, P on dry days is probably strongly controlled by local ET, leading to much stronger SM– P feedback on dry days ( Wei and

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D. Giard and E. Bazile

variables also acted to prevent long-term drifts with respect to the annual cycle inside the data assimilation procedure. In the meantime, a new land surface parameterization was developed at Météo-France, the so-called Interaction Soil Biosphere Atmosphere (ISBA) scheme ( Noilhan and Planton 1989 ; Noilhan and Mahfouf 1996 ). It has been extensively tested against field experiments (see Noilhan and Mahfouf 1996 for a short review) and behaves reasonably well in international comparison projects, as

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Daniel Fiifi Tawia Hagan, Guojie Wang, X. San Liang, and Han A. J. Dolman

1. Introduction The land surface plays an essential role in the climate system (e.g., Fischer et al. 2007 ; Miralles et al. 2014 ). A number of studies have demonstrated that the land–atmosphere interactions, especially soil moisture interactions with the atmosphere, have the potential to affect the occurrence of heat waves ( Stéfanon et al. 2014 ), drought ( Ciabatta et al. 2015 ; Roundy and Wood 2015 ), rainfall ( Taylor et al. 2012 ; Tuttle and Salvucci 2015 ), and floods ( Massari et al

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Min-Hui Lo, Wen-Ying Wu, Lois Iping Tang, Dongryeol Ryu, Mehnaz Rashid, and Ren-Jie Wu

1. Introduction Feedback between the land and the atmosphere is a critical component in the climate system. Understanding how land surface processes affect climate can help improve climate model simulations on the subseasonal to seasonal time scale. The relationship between soil moisture and surface water/energy fluxes is seen as the “terrestrial” segment of land–atmosphere coupling (interactions). The other segment, the “atmospheric” one, refers to the influence of surface fluxes on the

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Jessica M. Erlingis, Jonathan J. Gourley, and Jeffrey B. Basara

itself. Another possibility is that large sensible heat fluxes from dry soils can cause an increase in parcel buoyancy, allowing parcels to rise sufficiently to reach their level of free convection. Furthermore, land surface cover and/or states can have an effect on the properties of downstream precipitation ( Mo et al. 1997 ; Erlingis and Barros 2014 ) by modifying an air mass through energy and moisture exchanges with the surface. Given that land–atmosphere interactions can have such a nonlocal

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J-F. Mahfouf and J. Noilhan

soil moisture by the land surface scheme ISBA (interactions soil biosphere atmosphere)is in this way greatly improved.1. Introduction The need for accurate boundary conditions over continental surfaces in atmospheric numerical models isnow recognized, both for climate studies and numericalweather prediction (Rowntree 1991; Blondin 199l).Land surface schemes have been greatly improved during the last ten years. The influence of vegetation onsurface evaporation is now taken into account by

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John L. Williams III and Reed M. Maxwell

land surface-atmosphere interaction: A review based on observational and global modeling perspectives . J. Geophys. Res. , 101 ( D3 ), 7209 – 7225 . Chen, F. , and Avissar R. , 1994 : Impact of land-surface moisture variability on local shallow convective cumulus and precipitation in large-scale models . J. Appl. Meteor. , 33 , 1382 – 1401 . Chen, F. , and Dudhia J. , 2001 : Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I

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Hsi-Yen Ma, Heng Xiao, C. Roberto Mechoso, and Yongkang Xue

(AGCM) simulations with and without land–atmosphere interactions performed by Delworth and Manabe (1988 , 1989 ) demonstrated that the interactive treatment of soil moisture allows for larger variations in space and time of surface energy fluxes, thereby increasing the variance of surface air temperature. A series of AGCM ensemble simulations coordinated by the Global Land–Atmosphere Coupling Experiment (GLACE; Koster et al. 2004 , 2006 ) identified continental regions of strong coupling between

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