Modeling approaches to assimilating L band passive microwave observations over land surfaces

Abstract

[1] L band passive microwave remotely sensed data have great potential for providing estimates of soil moisture with high temporal sampling and on a regional scale. Several studies have shown the possibility of assessing the hydrological conditions deep down in soil (in the top 1 or 2 m) from these repetitive estimates of surface soil moisture. Water availability for plants, which is related to soil moisture in the root zone, is a key variable for estimating the evapotranspiration fluxes over land surfaces. This estimation is an important issue for meteorological and hydrological modeling, since it is a basic term of land surface forcing in mesoscale atmospheric circulations. However, at the present time the assimilation approach of remotely sensed brightness temperature data for operational use in the fields of meteorology and hydrology is poorly defined and important issues remain to be addressed in order to develop an operational assimilation approach. Two important issues are to identify (1) how vegetation variables describing vegetation development can be accounted for and (2) how the attenuation effects of L band microwave radiation within the canopy layer can be computed on large spatial scales. On the basis of an exhaustive data set including multiangular and dual-polarization passive microwave measurements acquired over a wheat crop during a 3-month period in 1993, two main modeling approaches are tested in this study. The principle of both approaches was based on the use of dual-polarization and multiangular observations to discriminate between the effects of soil and vegetation on the crop microwave signature. For the two approaches, both the initial soil water reservoir R 2 (at the beginning of the crop development) and parameterizations of the crop development could be retrieved simultaneously from the assimilation of the passive microwave measurements. From these results, promising assimilation strategies can be expected from the multiangular Soil Moisture and Ocean Salinity (SMOS) observations made over the land surface.

Future directions for advanced evapotranspiration modeling: Assimilation of remote sensing data into crop simulation models and SVAT models

“…This problem may be the major drawbacks for implementing variational assimilation procedures. It may be solved, at least in some situations, if a careful sensitivity analysis of the assimilation procedure is done in order to define precisely the parameters that should be retrieved or if some parameters are known from previous studies as for example in Wigneron et al (2002). Olioso et al (1999a,b) showed, with another model, that parameter compensations might be used on purpose for reducing the number of parameters to retrieve without affecting the accuracy of estimated evapotranspiration.…”

Using a multiobjective approach to retrieve information on surface properties used in a SVAT model

“…Cayrol et al (2000) assimilated series of AVHRR surface reflectances and temperatures to calibrate a coupled SVAT-Vegetation growth model. More recently, Wigneron et al (2002) assimilated L band passive brightness temperature in the ISBA-Ags model (Calvet et al, 1998), coupled with the Tau-Omega microwave radiative transfer model, in order to retrieve initial soil moisture and a parameter controlling vegetation growth.…”

Global soil moisture retrieval from a synthetic L‐band brightness temperature data set

“…Estimating this variable at the global scale has potential applications in hydrology and meteorology [Fennessy and Shukla, 1999;Dirmeyer, 2000;Leese et al, 2001]. Several studies showed that time series of surface soil moisture (wg) can be used to retrieve the rootzone soil moisture by using an assimilation algorithm [Entekhabi et al, 1994;Calvet and Noilhan, 2000;Wigneron et al, 2002a]. A number of airborne and ground-based experiments have shown that L-band passive microwave remotely sensed brightness temperatures (T B ) have great potential for providing estimates of wg.…”