An observing system simulation experiment for hydros radiometer-only soil moisture and freeze-thaw products

Abstract

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.

Emerging Methods to Validate Remotely Sensed Vegetation Water Content

“…Observing system simulation experiments (OSSEs) can reveal artifacts and errors due to the retrieval algorithm in translating microwave measurements into VOD at the respective instrument's scale (Figure 1) (Feldman, Chaparro, et al, 2021). While more commonly used for soil moisture retrievals (Crow et al, 2005), insights from OSSEs have shown satellite-based VOD errors positively correlate with soil moisture errors within simultaneous soil moisture and VOD retrievals (Konings et al, 2016;Zwieback et al, 2019). Additionally, most satellite measurement error tends to propagate more into VOD rather than soil moisture (Feldman, Chaparro, et al, 2021).…”

Accounting for Static and Dynamic Open Water in the Modeling of SMAP Brightness Temperatures Over Peatlands

“…T b stat : Static open water surfaces are assumed to be vegetation-free. Assuming that the temperature of the water surface equals the CLSM simulated temperature of the topsoil, the dielectric permittivity of water and subsequently T b stat is calculated assuming a smooth water surface [15].…”

A physically constrained inversion for high-resolution passive microwave retrieval of soil moisture and vegetation water content in L-band

“…This approach assumes that the vegetation optical depth τ is linearly related to the vegetation water content (VWC) as τ = b .VWC, where b typically varies between 0.05 to 6.0 m 2 kg -1 , depending on the vegetation type [36]. The algorithm estimates the VWC from 10-day climatology of NDVI through some regression equations [35,37,38] and a-prior knowledge of the plant's stem structure [39,40]. Having the optical depth, the vegetation transmissivity can be calculated as γ = exp (−τ sec φ), where φ denotes the radiometer incident angle in radians.…”