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Title: An observing system simulation experiment (OSSE) for the aquarius/SAC-D soil moisture product: An investigation of forward/retrieval model asymmetries

Author
item PERNA, P - Collaborator
item BRUSCANTINI, C - Collaborator
item FERRAZOLI, P - Collaborator
item GRINGIS, F - Collaborator
item KARSZENBAUM, H - Collaborator
item Crow, Wade

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/10/2012
Publication Date: 7/22/2012
Citation: Perna, P., Bruscantini, C., Ferrazoli, P., Gringis, F., Karszenbaum, H., Crow, W.T. 2012. An observing system simulation experiment (OSSE) for the aquarius/SAC-D soil moisture product: An investigation of forward/retrieval model asymmetries [abstract]. Proceedings of the 2012 International Geoscience & Remote Sensing Symposium, July 22-27, 2012, Munich, Germany. 2012 CDROM.

Interpretive Summary:

Technical Abstract: An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D mission is being developed for assessing the accuracy of soil moisture retrieval from passive and active L band remote sensing. This OSSE is able to capture the influence of different error sources: land surface heterogeneity, instrument noise and ancillary parameters uncertainties. In order to assess the impact of these error sources on the estimated volumetric soil moisture, a quantitative analysis is performed through the comparison between footprint-scale estimated soil moisture and high spatial resolution synthetic truth. The implementation of the OSSE is based on: (1) a 1-km land surface model, (2) a forward microwave emission model to simulate the radiometer observations, (3) an orbital and sensor model to simulate Aquarius observations and (4) a retrieval model. The current simulation implements a first order radiative transfer solution as a forward and inverse models (using direct inversion). So far, this OSSE has been successfully exploited to study the artifacts in the retrieved soil moisture associated to uncertainties and the aggregation of the ancillary parameters needed for the retrieval. However, a major concern about the validity of this approach is associated to the basic assumptions related to the forward model. The emissivity of real surfaces is very complex, is strongly dependent on landcover type and condition and cannot be completely modeled with a simple model. In particular, surface covered by average to dense vegetation presents complex scattering properties, strongly related to canopy structure. With the objective of fully capture the difficulties related to the soil moisture retrieval from passive data, in this paper the forward model was implemented using a theoretical approach based on the electromagnetic modeling of vegetation elements and high order radiative transfer theory. As expected, both model present different values of brightness temperature for the same surface condition, and the maximum discrepancies correspond to the most vegetated areas. These discrepancies are explained as a function of the different fundamental hypothesis of the models.