The error structure of the SMAP single and dual channel soil moisture retrievals.
Geophys Res Lett
; 45(2): 758-765, 2018 Jan 28.
Article
en En
| MEDLINE
| ID: mdl-32848287
Knowledge of the temporal error structure for remotely sensed surface soil moisture retrievals can improve our ability to exploit them for hydrologic and climate studies. This study employs a triple collocation analysis to investigate both the total variance and temporal auto-correlation of errors in Soil Moisture Active and Passive (SMAP) products generated from two separate soil moisture retrieval algorithms, the vertically-polarized brightness temperature based Single Channel Algorithm (SCA-V, the current baseline SMAP algorithm) and the Dual Channel Algorithm (DCA). A key assumption made in SCA-V is that real-time vegetation opacity can be accurately captured using only a climatology for vegetation opacity. Results demonstrate that, while SCA-V generally outperforms DCA, SCA-V can produce larger total errors when this assumption is significantly violated by inter-annual variability in vegetation health and biomass. Furthermore, larger auto-correlated errors in SCA-V retrievals are found in areas with relatively large vegetation opacity deviations from climatological expectations. This implies that a significant portion of the auto-correlated error in SCA-V is attributable to the violation of its vegetation opacity climatology assumption and suggests that utilizing a real (as opposed to climatological) vegetation opacity time series in the SCA-V algorithm would reduce the magnitude of auto-correlated soil moisture retrieval errors.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Geophys Res Lett
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Estados Unidos