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1. Introduction The interaction between the surface layer and lower atmospheric layers is important for weather and climate models. The role of land–atmosphere interactions becomes even more important over a warm, moist surface covered by different vegetation types ( Ek et al. 2003 ; Dirmeyer et al. 2010 ). The value of improving land surface models to enhance operational forecasts is recognized by the different numerical weather prediction (NWP) centers (e.g., Beljaars et al. 1996 ; Betts
1. Introduction The interaction between the surface layer and lower atmospheric layers is important for weather and climate models. The role of land–atmosphere interactions becomes even more important over a warm, moist surface covered by different vegetation types ( Ek et al. 2003 ; Dirmeyer et al. 2010 ). The value of improving land surface models to enhance operational forecasts is recognized by the different numerical weather prediction (NWP) centers (e.g., Beljaars et al. 1996 ; Betts
1. Introduction It is a standard practice in modeling land surface–atmosphere interaction that momentum or scalar fluxes can be parameterized by relating them to the mean velocity gradient or scalar concentration gradient by means of a turbulent diffusion coefficient, called gradient-diffusion parameterization or K theory ( Raupach and Thom 1981 ; Katul et al. 2013 ). The K theory has enjoyed a high degree of popularity over the years, especially because of the ease of usage. It has been
1. Introduction It is a standard practice in modeling land surface–atmosphere interaction that momentum or scalar fluxes can be parameterized by relating them to the mean velocity gradient or scalar concentration gradient by means of a turbulent diffusion coefficient, called gradient-diffusion parameterization or K theory ( Raupach and Thom 1981 ; Katul et al. 2013 ). The K theory has enjoyed a high degree of popularity over the years, especially because of the ease of usage. It has been
(b) locations of the meteorological stations (red dots) in the inner domain. The shaded contour represents topography height (m), the black labels represent the major provinces, and the blue labels represent the names of the observational sites. In this study, the main physical-parameterization schemes contain the Noah land surface scheme to describe the detailed thermodynamic and hydrological processes of land–atmosphere interactions ( Chen et al. 2006 ; Ek et al. 2003 ), the Lin microphysics
(b) locations of the meteorological stations (red dots) in the inner domain. The shaded contour represents topography height (m), the black labels represent the major provinces, and the blue labels represent the names of the observational sites. In this study, the main physical-parameterization schemes contain the Noah land surface scheme to describe the detailed thermodynamic and hydrological processes of land–atmosphere interactions ( Chen et al. 2006 ; Ek et al. 2003 ), the Lin microphysics
( Bruijnzeel and Proctor 1993 ). These studies indicate that fog precipitation is probably more important for the vegetation than rainfall in arid and semiarid coastal areas. Many numerical models have been proposed to estimate the cloud water deposition on the canopy. These models have been based on the cloud water deposition model formulated by Lovett (1984) , hereinafter referred to as the Lovett model. The Lovett model is a multilayer model for atmosphere–vegetation interaction that contains equations
( Bruijnzeel and Proctor 1993 ). These studies indicate that fog precipitation is probably more important for the vegetation than rainfall in arid and semiarid coastal areas. Many numerical models have been proposed to estimate the cloud water deposition on the canopy. These models have been based on the cloud water deposition model formulated by Lovett (1984) , hereinafter referred to as the Lovett model. The Lovett model is a multilayer model for atmosphere–vegetation interaction that contains equations
. Schwerdtfeger , J. M. Hacker , I. J. Foster , and R. C. G. Smith , 1993 : Land–atmosphere interaction in a semiarid region: The bunny fence experiment . Bull. Amer. Meteor. Soc. , 74 , 1327 – 1334 , doi:10.1175/1520-0477(1993)074<1327:LIIASR>2.0.CO;2 . Mahfouf , J. F. , E. Richard , and P. Mascart , 1987 : The influence of soil and vegetation on the development of mesoscale circulations . J. Climate Appl. Meteor. , 26 , 1483 – 1495 , doi:10.1175/1520-0450(1987)026<1483:TIOSAV>2
. Schwerdtfeger , J. M. Hacker , I. J. Foster , and R. C. G. Smith , 1993 : Land–atmosphere interaction in a semiarid region: The bunny fence experiment . Bull. Amer. Meteor. Soc. , 74 , 1327 – 1334 , doi:10.1175/1520-0477(1993)074<1327:LIIASR>2.0.CO;2 . Mahfouf , J. F. , E. Richard , and P. Mascart , 1987 : The influence of soil and vegetation on the development of mesoscale circulations . J. Climate Appl. Meteor. , 26 , 1483 – 1495 , doi:10.1175/1520-0450(1987)026<1483:TIOSAV>2
study under heterogeneous conditions asked two main questions: 1) How is the induced mesoscale circulation represented by MM5, as compared with DALES? 2) Are the modeled surface fluxes in MM5 influenced by the induced mesoscale circulation (atmosphere–land interactions)? To the best of our knowledge, this is the first time that a mesoscale model and an LES have been compared using control numerical simulations with identical surface forcing. The paper is structured as follows. The models under study
study under heterogeneous conditions asked two main questions: 1) How is the induced mesoscale circulation represented by MM5, as compared with DALES? 2) Are the modeled surface fluxes in MM5 influenced by the induced mesoscale circulation (atmosphere–land interactions)? To the best of our knowledge, this is the first time that a mesoscale model and an LES have been compared using control numerical simulations with identical surface forcing. The paper is structured as follows. The models under study
scheme ISBA-DF (where DF stands for diffusion; Boone 2000 ; Boone et al. 1999 ). e. COBEL-Noah The atmospheric model is a modified version of the high-resolution COBEL model described in Bergot and Guedalia (1994) . The main modifications concern the turbulence scheme and the parameterization of the interaction between the soil and the atmosphere ( Mueller et al. 2005 ). The vertical resolution is defined by 30 levels in the lowest 200 m. The surface scheme is the Noah land surface model ( Chen et
scheme ISBA-DF (where DF stands for diffusion; Boone 2000 ; Boone et al. 1999 ). e. COBEL-Noah The atmospheric model is a modified version of the high-resolution COBEL model described in Bergot and Guedalia (1994) . The main modifications concern the turbulence scheme and the parameterization of the interaction between the soil and the atmosphere ( Mueller et al. 2005 ). The vertical resolution is defined by 30 levels in the lowest 200 m. The surface scheme is the Noah land surface model ( Chen et
reflective paint—are seen as an urban heat-mitigation option ( Santamouris 2014 ). They reflect incoming solar radiation more efficiently than darker roofs, reducing the amount of heat that is absorbed by the rooftop and the building itself and ultimately transferred to the atmosphere ( Kalkstein et al. 2013 ). This was demonstrated in an observational study of cool roofs in Melbourne in which the net radiation at midday was 78% lower than for a vegetated rooftop during summer ( Coutts et al. 2013
reflective paint—are seen as an urban heat-mitigation option ( Santamouris 2014 ). They reflect incoming solar radiation more efficiently than darker roofs, reducing the amount of heat that is absorbed by the rooftop and the building itself and ultimately transferred to the atmosphere ( Kalkstein et al. 2013 ). This was demonstrated in an observational study of cool roofs in Melbourne in which the net radiation at midday was 78% lower than for a vegetated rooftop during summer ( Coutts et al. 2013
1. Introduction Vegetation cover influences the land–atmosphere exchanges of water, energy, and carbon (e.g., Dickinson et al. 1986 ; Sellers et al. 1996 ; Bonan 1996 ; Dai et al. 2003 ). Green vegetation fraction (GVF; Deardorff 1978 ) is widely used in global models along with many other applications such as studies of land-cover (LC) change. Along with leaf area index (LAI; Myneni et al. 2002 ), GVF is used to describe the abundance of vegetation in most global models. Some models
1. Introduction Vegetation cover influences the land–atmosphere exchanges of water, energy, and carbon (e.g., Dickinson et al. 1986 ; Sellers et al. 1996 ; Bonan 1996 ; Dai et al. 2003 ). Green vegetation fraction (GVF; Deardorff 1978 ) is widely used in global models along with many other applications such as studies of land-cover (LC) change. Along with leaf area index (LAI; Myneni et al. 2002 ), GVF is used to describe the abundance of vegetation in most global models. Some models
global climate change detection. J. Climate , 13 , 3187 – 3205 . Dai , A. , K. E. Trenberth , and T. Qian , 2004 : A global dataset of Palmer drought severity index for 1870–2002: Relationship with soil moisture and effects of surface warming. J. Hydrometeor. , 5 , 1117 – 1130 . Diffenbaugh , N. S. , 2005 : Atmosphere–land cover feedbacks alter the response of surface temperature to CO 2 forcing in the western United States. Climate Dyn. , 24 , 237 – 251 . Easterling , D. R
global climate change detection. J. Climate , 13 , 3187 – 3205 . Dai , A. , K. E. Trenberth , and T. Qian , 2004 : A global dataset of Palmer drought severity index for 1870–2002: Relationship with soil moisture and effects of surface warming. J. Hydrometeor. , 5 , 1117 – 1130 . Diffenbaugh , N. S. , 2005 : Atmosphere–land cover feedbacks alter the response of surface temperature to CO 2 forcing in the western United States. Climate Dyn. , 24 , 237 – 251 . Easterling , D. R
