Abstract

Numerous studies have estimated surface heat fluxes by assimilating land surface temperature (LST) observations (as the state variable of land surface). A number of other studies have focused on the estimation of surface energy balance components by assimilating air temperature and specific humidity (as the state variables of atmosphere) into an atmospheric boundary layer model. This study advances these existing data assimilation approaches by the synergistic assimilation of LST, air temperature, and specific humidity into a coupled land surface-atmospheric boundary layer model. The unknown parameters are the neutral bulk heat transfer coefficient (CHN) and evaporative fraction (EF). CHN scales the sum of turbulent heat fluxes, and EF represents their partitioning. The developed approach is tested at the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) site in the summer of 1987 and 1988. The results indicate that the new approach performs well in both wet and dry periods because it uses the implicit information in both the land surface and atmospheric state variables (i.e., LST, air temperature, and specific humidity). The root-mean-square-errors (RMSEs) of estimated daily sensible and latent heat fluxes are 21.80 Wm−2 (22.10 Wm−2) and 39.32 Wm−2 (36.89 Wm−2) for FIFE 87 (88). The corresponding mean-absolute-percentage-errors (MAPEs) are 22.16% (18.64%) and 13.98% (13.44%) for FIFE 87 (88). The new variational data assimilation (VDA) system outperforms the previous studies that assimilated either LST or air temperature/specific humidity. For FIFE 87, this study decreases the RMSEs of daily sensible and latent heat fluxes estimates by 12.5% and 24.4% compared to assimilating only LST, and by 15.2% and 26.7% compared to assimilating only air temperature and specific humidity. A similar improvement is obtained for FIFE 88. The atmospheric boundary layer height, potential temperature, and specific humidity estimates from the VDA approach are also in good agreement with the corresponding radiosonde observations, and can capture their variations during the course of the day.

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