CONICET | Buscador de Institutos y Recursos Humanos

Knowledge of surface soil moisture (SSM) spatio-temporal dynamics is essential for many practical applications such as weather forecasting, Óoods/drought monitoring and water resource management. SSM is particularly relevant over climate transition regions such as southeastern South America (SESA), a recognized land-atmosphere interaction hotspot by studies using climate models and more recently remote sensing products (RSPs).SESA has the largest population density of the continent and is the most productive region in terms of agriculture, livestock and industry. It comprises the low and Óat Pampas plains where the most severe subtropical storms of the globe are developed, making SESA an interesting region for studying SSM. A novel framework for studying SSM dynamics over the SESA hotspot is presented. SSM dry-downs during non-rainy days after precipitation events are studied on scales of the landscape. This is an essential knowledge to better understand how the surface will respond to changes in the characteristics of rainfall. The dry-down is critical for soil moisture stress of plants, surface Bowen ratio, surface warming and atmospheric response.The ORCHIDEE land surface model and the recent version of SMOS RSP (v.620) were chosen since they are particularly suited for this study. ORCHIDEE provides a high vertical resolution of the soil surface, making it suitable for comparison with RSPs. SMOS uses L-band, which is suitable for densely vegetated areas like SESA and the v.620 includes a new parameterization for forested areas that reduces uncertainties and improves the data quality Òltering.ORCHIDEE and SMOS daily data are employed at 25 km for summers in 2010-2014. Results are analyzed in terms of soil and land cover characteristics, sampling frequency, observational uncertainties and also compared to other metrics.

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