An important issue in the development of a dedicated space borne soil moisture sensor has been concern over the reliability of soil moisture retrievals in densely vegetated areas and the global extent over which retrievals will be possible. Errors in retrieved soil moisture can originate from a variety of sources within the measurement and retrieval process. In addition to instrument error, three key contributors to retrieval error are the masking of the soil microwave signal by vegetation, the interplay between nonlinear retrieval physics and the relatively poor spatial resolution of space borne sensors, and retrieval parameter uncertainty. Quantification of these errors requires the realistic specification of land surface soil moisture heterogeneity and spatial vegetation patterns. Since detailed soil moisture patterns are currently difficult to obtain from direct observations, an attractive alternative is the application of an observing system simulation experiment (OSSE) in which simulated land surface states are propagated through the sensor measurement and retrieval process to investigate and constrain expected levels of retrieval error. This manuscript describes results from an OSSE designed out to simulate the impact of land surface heterogeneity, instrument error, and retrieval parameter uncertainty on radiometer-only soil moisture products derived from the NASA ESSP Hydrosphere State (Hydros) mission.
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