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hydrologic and atmospheric model performance ( Betts 2004 , 2009 ). By linking the surface, PBL, and cloud processes, coupling encompasses complex cross-scale interactions that determine the climate state. Coupling strength varies on local (5–10 km) to regional scales (400 km) and temporally on daily to weekly time scales ( Betts 2004 ; Koster et al. 2003 ; Taylor and Ellis 2006 ), modulated by background synoptic weather (i.e., convergence/divergence, monsoons, and cloud fields) and larger scale (i
hydrologic and atmospheric model performance ( Betts 2004 , 2009 ). By linking the surface, PBL, and cloud processes, coupling encompasses complex cross-scale interactions that determine the climate state. Coupling strength varies on local (5–10 km) to regional scales (400 km) and temporally on daily to weekly time scales ( Betts 2004 ; Koster et al. 2003 ; Taylor and Ellis 2006 ), modulated by background synoptic weather (i.e., convergence/divergence, monsoons, and cloud fields) and larger scale (i
land models and different elevations? Such formulations, however, have a minimal effect on nighttime T s . There are two questions relevant to the nighttime T s and the interplay between sensible and ground heat fluxes: How can the sensible heat flux be constrained under stable (atmospheric stratification) conditions in measurements and modeling? And how can the computation of ground heat flux be constrained in land modeling? The goal of this study is to improve the modeling of surface skin
land models and different elevations? Such formulations, however, have a minimal effect on nighttime T s . There are two questions relevant to the nighttime T s and the interplay between sensible and ground heat fluxes: How can the sensible heat flux be constrained under stable (atmospheric stratification) conditions in measurements and modeling? And how can the computation of ground heat flux be constrained in land modeling? The goal of this study is to improve the modeling of surface skin
