Multispectral satellite data in the context of land surface heat balance

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Abstract
Any realistic study of the Earth's climate must consider thermal interaction between the atmosphere and the land surface. During the past few years, several highly sophisticated models have been developed to describe exchanges of radiation, heat, and momentum between the land surface and the atmosphere at mesoscales and global scales. These models need to be supplemented by high‐quality global measurements at varying spatial and temporal scales of physical and biological states of the land surface. Global data sets are needed for surface parameters used to describe the processes and also to initialize and validate the time evolution of surface characteristics predicted by the model. Observations in different spectral bands by instruments on board satellites can provide spatially representative values for some of the fluxes and radiative characteristics of the surface, from which the parameters needed for heat balance modeling have to be derived. Development of these data sets presents considerable difficulty because the relations between radiative and physical characteristics are generally nonlinear and nonunique; the radiative characteristic in any spectral band is generally determined by several physical characteristics. Relationships between different spectral observations can be used to develop hypotheses concerning the relative importance of different land surface parameters determining these observations, which would have to be confirmed by field observations. Satellite observations for visible, near‐infrared, infrared, and microwave bands to estimate the fluxes at the surface (radiative, soil, sensible, and latent heat) and surface characteristics (albedo, surface temperature, vegetation parameters, and soil moisture) are presented. Interannual variations of some of these satellite observations are discussed in relation to land surface change. A better understanding needs to be developed regarding the interpretation of infrared temperature observations as they relate to the temperature determined by the heat balance equation. Further study is needed to explore more effective use of remotely sensed data for vegetation in heat balance modeling.