Leveraging microwave polarization information for the calibration of a land data assimilation system

摘要: This letter contributes a new approach to calibrating tau-omega radiative transfer model coupled land surface output with low-frequency (<10 GHz) microwave brightness temperature (TB) observations. The problem of this system is generally poorly posed because various parameter combinations may yield indistinguishable (least squares error) results. theoretically important for data assimilation since alternative have different impacts on the sensitivity TB soil moisture and misattribution systematic error therefore disrupt performance. Via synthetic experiments we demonstrate that using polarization difference parameterize vegetation opacity can improve stability calibrated moisture/TB sensitivities relative more typical utilizing ancillary information estimate opacity. proposed fully follows from model, implemented according commonly adopted assumptions, reduces by one number calibration parameters.