Drusch, M. | Search NASA

NASA NTRS2014

Microwave Interferometric Radiometry in Remote Sensing: an Invited Historical Review

The launch of the Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009 marked a milestone in remote sensing for it was the first time a radiometer capable of acquiring wide field of view images at every single snapshot, a unique feature of the synthetic aperture technique, made it to space. The technology behind such an achievement was developed, thanks to the effort of a community of researchers and engineers in different groups around the world. It was only because of their joint work that SMOS finally became a reality. The fact that the European Space Agency, together with CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnológico e Industrial), managed to get the project through should be considered a merit and a reward for that entire community. This paper is an invited historical review that, within a very limited number of pages, tries to provide insight into some of the developments which, one way or another, are imprinted in the name of SMOS.

Microwave↗

NASA NTRS2014

Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin, USA

The Soil Moisture and Ocean Salinity (SMOS) satellite mission is routinely providing global multi-angular observations of brightness temperature (TB) at both horizontal and vertical polarization with a 3-day repeat period. The assimilation of such data into a land surface model (LSM) may improve the skill of operational flood forecasts through an improved estimation of soil moisture (SM). To accommodate for the direct assimilation of the SMOS TB data, the LSM needs to be coupled with a radiative transfer model (RTM), serving as a forward operator for the simulation of multi-angular and multi-polarization top of atmosphere TBs. This study investigates the use of the Variable Infiltration Capacity (VIC) LSM coupled with the Community Microwave Emission Modelling platform (CMEM) for simulating SMOS TB observations over the Upper Mississippi basin, USA. For a period of 2 years (2010-2011), a comparison between SMOS TBs and simulations with literature-based RTM parameters reveals a basin averaged bias of 30K. Therefore, time series of SMOS TB observations are used to investigate ways for mitigating these large biases. Specifically, the study demonstrates the impact of the LSM soil moisture climatology in the magnitude of TB biases. After CDF matching the SM climatology of the LSM to SMOS retrievals, the average bias decreases from 30K to less than 5K. Further improvements can be made through calibration of RTM parameters related to the modeling of surface roughness and vegetation. Consequently, it can be concluded that SM rescaling and RTM optimization are efficient means for mitigating biases and form a necessary preparatory step for data assimilation.

SMOS↗