IAFE   05512
INSTITUTO DE ASTRONOMIA Y FISICA DEL ESPACIO
Unidad Ejecutora - UE
artículos
Título:
An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D soil moisture product
Autor/es:
CINTIA BRUSCANTINI; WADE CROW; FRANCISCO GRINGS; PABLO PERNA; MARTIN MAAS; HAYDEE KARSZENBAUM
Revista:
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Editorial:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Referencias:
Lugar: Albuquerque; Año: 2014 p. 12 - 23
ISSN:
0196-2892
Resumen:
An Observing System Simulation Experiment for the Aquarius/SAC-D mission has been developed for assessing the accuracy of soil moisture retrievals from passive L-band remote sensing. The implementation of the OSSE is based on the following: a 1-km land surface model over the Red-Arkansas River Basin, a forward microwave emission model to simulate the radiometer observations, a realistic orbital and sensor model to resample the measurements mimicking Aquarius operation, and an inverse soil moisture retrieval model. The simulation implements a zero-order radiative transfer model. Retrieval is performed by direct inversion of the forward model. The Aquarius OSSE attempts to capture the influence of various error sources, such as land surface heterogeneity, instrument noise and retrieval ancillary parameter uncertainty, all on the accuracy of Aquarius surface soil moisture retrievals. In order to assess the impact of these error sources on the estimated volumetric soil moisture, a quantitative error analysis is performed by comparison of footprint-scale synthetic soil moisture with ?true? soil moisture fields obtained from the direct aggregation of the original 1-km soil moisture field input to the forward model. Results show that, in heavily vegetated areas, soil moisture retrievals have a positive bias that can be suppressed with an alternative aggregation strategy for ancillary parameter vegetation water content (VWC). Retrieval accuracy was also evaluated when adding errors to 1-km VWC (which are intended to account for errors in VWC derived from remote sensing data). For soil moisture retrieval RMSE of the order of 0.05 m3=m3, error in VWC should be less than 12%.