An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations

Abstract Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply constant, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, and 0.96 for bare soil as in the National Center for Atmospheric Research (NCAR) Community Land Model version 2 (CLM2). This is the so-called constant-emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the constant emissivity induces errors in modeling the surface energy budget, especially over large arid and semiarid areas where ɛ is far smaller than unity. One feasible solution to this problem is to apply the satellite-based broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities (ɛλ) in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity (ɛ) required by land surface models. The observed emissivity data show strong seasonality and land-cover dependence. Specifically, emissivity depends on surface-cover type, soil moisture content, soil organic composition, vegetation density, and structure. For example, broadband ɛ is usually around 0.96–0.98 for densely vegetated areas (leaf area index) LAI 2, but it can be lower than 0.90 for bare soils (e.g., desert). To examine the impact of variable surface broadband emissivity, sensitivity studies were conducted using offline CLM2 and coupled NCAR Community Atmosphere Models, CAM2–CLM2. These sensitivity studies illustrate that large impacts of surface ɛ occur over deserts, with changes up to 1°–2°C in ground temperature, surface skin temperature, and 2-m surface air temperature, as well as evident changes in sensible and latent heat fluxes.