Interpretation of ASCAT Radar Scatterometer Observations Over Land: A Case Study Over Southwestern France

Abstract

This paper investigates to what extent soil moisture and vegetation density information can be extracted from the Advanced Scatterometer (ASCAT) satellite-derived radar backscatter (σ°) in a data assimilation context. The impact of independent estimates of the surface soil moisture (SSM) and leaf area index (LAI) of diverse vegetation types on ASCAT σ° observations is simulated over southwestern France using the water cloud model (WCM). The LAI and SSM variables used by the WCM are derived from satellite observations and from the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model, respectively. They permit the calibration of the four parameters of the WCM describing static soil and vegetation characteristics. A seasonal analysis of the model scores shows that the WCM has shortcomings over karstic areas and wheat croplands. In the studied area, the Klaus windstorm in January 2009 damaged a large fraction of the Landes forest. The ability of the WCM to represent the impact of Klaus and to simulate ASCAT σ° observations in contrasting land-cover conditions is explored. The difference in σ° observations between the forest zone affected by the storm and the bordering agricultural areas presents a marked seasonality before the storm. The difference is small in the springtime (from March to May) and large in the autumn (September to November) and wintertime (December to February). After the storm, hardly any seasonality was observed over four years. This study shows that the WCM is able to simulate this extreme event. It is concluded that the WCM could be used as an observation operator for the assimilation of ASCAT σ° observations into the ISBA land surface model.

Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

“…where A, B, C, D, V 1 and V 2 are parameters of the WCM model. The two latter ones represent the effect of the vegetation on the radar backscattering [74]. In the original formulation of the WCM, V 1 equals to 1 [43].…”

An Ensemble Square Root Filter for the joint assimilation of surface soil moiture and leaf area index within LDAS-Monde: application over the Euro-Mediterranean region

“…LDAS-Monde would benefit from having observations linked to vegetation available every day. This is the case of radar backscatter coefficients as shown by Lievens et al (2017) and Shamambo et al (2019) https://doi.org/10.5194/hess-2019-391 Preprint. Discussion started: 20 August 2019 c Author(s) 2019.…”

An ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean region

“…It raises the question of the quality of ISBA and/or SSM observations (after seasonal linear rescaling) in arid places. Stoffelen et al (2017) have shown that observed SSM derived from scatterometers can have poor quality in arid places. Further studies of such aspects are beyond the scope of this paper.…”