Towards the Removal of Model Bias from ESA CCI SM by Using an L-Band Scaling Reference

Constructing long time records of soil moisture (SM) requires the merging of data derived from different instruments while insuring the removing of the bias from different sensors time series. For instance, the ESA Climate Change Initiative (CCI) for SM currently uses the GLDAS v2.1 model as the reference to re-scale active and passive microwave time series. This paper discusses the possibility to use data from an L-band sensor as the reference in order to remove model dependency. AMSR-2 SM time series were re-scaled using different SMAP and SMOS datasets and evaluated against in-situ measurements. The results show that L-band data can be used to re-scale other sensor data with good performances. In addition, using the 11-years SMOS SM times series, the optimal length of the reference time series was studied.