Scale issues in land-atmosphere interactions: implications for remote sensing of the surface energy balance

Abstract The interaction between the land surface and the atmosphere is discussed focusing on the recent literature. Of primary importance is the issue of scale and the variation across different levels of pixel resolution for using remotely sensed data in the determination of the different components of the surface energy balance (SEB). This leads into a discussion of various methods of aggregating local scale input parameters in order to calculate larger scale surface fluxes. As an example application, airborne and satellite data are coupled to a soil-vegetation–atmosphere-transfer (SVAT) model and applied to the Southern Great Plains 1997 (SGP97) Hydrology Experiment. A physically based aggregation scheme is suggested for radiometric temperature by decomposing the temperature into vegetation and soil components and then aggregating the radiance field based on the percent cover of vegetation. Fluxes derived from the airborne data agree well with those measured with eddy covariance stations. Satellite data agrees poorly with the surface and airborne estimates. However, after aggregating the airborne data to the resolution of the satellite, the agreement is better. This suggests that the satellite data is useful at estimating the fluxes at the 1 km 2 scale, while the comparison between the 1 km 2 satellite and the surface data may be problematic at such scales.

[1]  Robert E. Dickinson,et al.  An approach to deriving roughness length and zero-plane displacement height from satellite data, prototyped with BOREAS data , 2000 .

[2]  Yann Kerr,et al.  Estimation of sensible heat flux over sparsely vegetated surfaces , 1997 .

[3]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .

[4]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[5]  R. Koster,et al.  Modeling the land surface boundary in climate models as a composite of independent vegetation stands , 1992 .

[6]  W. Kustas,et al.  Impact of Using Different Time-Averaged Inputs for Estimating Sensible Heat Flux of Riparian Vegetation Using Radiometric Surface Temperature , 2002 .

[7]  Le Jiang,et al.  Approaches for Aggregating Heterogeneous Surface Parameters and Fluxes for Mesoscale and Climate Models , 1999 .

[8]  Marc B. Parlange,et al.  Natural integration of scalar fluxes from complex terrain , 1999 .

[9]  K. McNaughton,et al.  A mixed-layer model for regional evaporation , 1986 .

[10]  M. S. Moran,et al.  The scaling characteristics of remotely-sensed variables for sparsely-vegetated heterogeneous landscapes , 1997 .

[11]  Bruno Monteny,et al.  Effective parameters of surface energy balance in heterogeneous landscape , 1994 .

[12]  M. Parlange,et al.  Surface length scales and shear stress: Implications for land‐atmosphere interaction over complex terrain , 1999 .

[13]  Bin Li,et al.  The impact of spatial variability of land-surface characteristics on land-surface heat fluxes , 1994 .

[14]  A. Cracknell.  Review article Synergy in remote sensing-what's in a pixel? , 1998 .

[15]  Yann Kerr,et al.  Methods to aggregate turbulent fluxes over heterogeneous surfaces: application to SALSA data set in Mexico , 2000 .

[16]  Bruno Monteny,et al.  Sensible heat flux and radiometric surface temperature over sparse Sahelian vegetation II. A model for the kB−1 parameter , 1997 .

[17]  Monique Y. Leclerc,et al.  Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation , 1990 .

[18]  F. Giorgi,et al.  An Approach for the Representation of Surface Heterogeneity in Land Surface Models. Part I: Theoretical Framework , 1997 .

[19]  Mark A. Friedl,et al.  Forward and inverse modeling of land surface energy balance using surface temperature measurements , 2002 .

[20]  Charlotte Bay Hasager,et al.  Surface‐flux aggregation in heterogeneous terrain , 1999 .

[21]  T. Jackson,et al.  The impact on area‐averaged heat fluxes from using remotely sensed data at different resolutions: A case study with Washita '92 data , 1999 .

[22]  Patch scale aggregation of heterogeneous land surface cover for mesoscale meteorological models , 1997 .

[23]  H. Tennekes,et al.  A Model for the Dynamics of the Inversion Above a Convective Boundary Layer , 1973 .

[24]  M. S. Moran,et al.  Determination of sensible heat flux over sparse canopy using thermal infrared data , 1989 .

[25]  T. Carlson,et al.  Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models , 1995 .

[26]  Jielun Sun,et al.  Relationship of surface heat flux to microscale temperature variations: Application to boreas , 1995 .

[27]  William P. Kustas,et al.  Large‐eddy simulation over heterogeneous terrain with remotely sensed land surface conditions , 2001 .

[28]  Nathaniel A. Brunsell,et al.  Incorporating Surface Emissivity into a Thermal Atmospheric Correction , 2002 .

[29]  Zong-Liang Yang,et al.  Implementing surface parameter aggregation rules in the CCM3 global climate model: Regional responses at the land surface , 1999 .

[30]  L. Mahrt.  Surface Heterogeneity and Vertical Structure of the Boundary Layer , 2000, Boundary-Layer Meteorology.

[31]  J. Finnigan,et al.  Scale issues in boundary-layer meteorology: Surface energy balances in heterogeneous terrain , 1995 .

[32]  Nathaniel A. Brunsell,et al.  Length Scale Analysis of Surface Energy Fluxes Derived from Remote Sensing , 2003 .

[33]  Zong-Liang Yang,et al.  Aggregation rules for surface parameters in global models , 1997 .

[34]  W. Shuttleworth,et al.  Macrohydrology ― the new challenge for process hydrology , 1988 .

[35]  Jielun Sun,et al.  Determination of Surface Fluxes from the Surface Radiative Temperature , 1995 .

[36]  Roni Avissar,et al.  Representation of heterogeneity effects in Earth system modeling: Experience from land surface modeling , 1997 .

[37]  Thomas J. Jackson,et al.  Verification of Patch- and Regional-Scale Energy Balance Estimates Derived from Microwave and Optical Remote Sensing during SGP97 , 2001 .

[38]  S. Zilitinkevich.  Comments on “A Model for the Dynamics of the Inversion Above a Convective Boundary Layer” , 1975 .

[39]  P. J. Mason,et al.  The formation of areally‐averaged roughness lengths , 1988 .

[40]  F. Giorgi,et al.  An Approach for the Representation of Surface Heterogeneity in Land Surface Models. Part II: Validation and Sensitivity Experiments , 1997 .

[41]  Monique Y. Leclerc,et al.  How large must surface inhomogeneities be before they influence the convective boundary layer structure? A case study , 1995 .