Surface roughness parameters estimation over the Tibetan Plateau: Optimization, calibration and validation in the dense soil moisture networks

Surface roughness has significate impacts on the land surface microwave emission and is an important process that should be considered in the development of soil moisture retrieval algorithm. The surface roughness can be descripted by two parameters: rms height (h) and correlation length (l), with a distribution function either in Gaussian or exponential form. These two parameters can be observed at field scale (1m ∼ 10 m) by using roughmeters, but they are hard to measure at the scale of satellite footprint (∼ 40 km). Currently, in the most of current soil moisture retrieval algorithm, the surface roughness parameters are either set as constant values or obtained from limited in situ observation. Consequently, the space heterogeneity of land surface roughness is not well handled. In this study, we developed a systemic method to estimate surface roughness parameters at satellite footprint scale and apply it to retrieve surface soil moisture over the Tibetan Plateau from AMSR-E/AMSR2 observation. At the first step, we optimized the surface roughness parameter over the Tibetan Plateau with using land surface model simulation and time series of microwave observation. At the same time, based on the accurate soil temperature moisture observations obtained at the Naqu dense soil network, surface roughness parameters were calibrated by using a radiative transfer model in which AIME was used. Finally, a regression relationship was developed between the optimized parameters and calibrated parameters and applied to correct the optimized parameter over whole Tibetan Plateau. With the new surface roughness parameters set, soil moisture over Tibetan Plateau was retrieved from AMSR-E/AMSR2 observation and validated at other two dense soil network: Maqu and Yadong. The study is carrying out now, more details will be reported in the conference.