Location: Hydrology and Remote Sensing Laboratory
Project Number: 8042-13610-028-66
Start Date: Jan 01, 2014
End Date: Dec 31, 2014
The Auto-Tuned Land Assimilation System (ATLAS) is a recently-developed USDA ARS algorithm for estimating the statistical properties of error in remotely-sensed surface soil moisture retrievals. The technique is based on the merging of an adaptive Kalman Filter and triple collocation analysis and - unlike any existing validation approach - is robust to the presence of both auto-correlated and cross-correlated errors in remotely-sensed surface soil moisture products. As a result, it represents the state-of-the-art in terms of validating remotely-sensed soil moisture retrievals over large areas of the world in which ground-based soil moisture observations are not available. In this project, ARS will globally apply ATLAS using three separate soil moisture products (a water balance-based product, an active microwave satellite product and a passive microwave satellite product) in order to access errors in (both of the) the satellite-based products. This assessment will, in turn, be used by the European Space Agency (ESA) to validate an Essential Climate Variable (ECV) data product currently being developed based on satellite-derived surface soil moisture retrievals.