Surface soil moisture spatio-temporal dynamics in southeastern South America observed by SMOS and modeled by ORCHIDEE

SÖRENSSON, ANNA; RUSCICA, ROMINA; KARSZENBAUM HAYDEE; POLCHER, JAN; SALVIA, MARÍA MERCEDES; MARIA PILES

Viena

Workshop; 4th Satellite Soil Moisture Validation and Application Workshop; 2017

Understanding surface soil moisture (SSM) spatio-temporal dynamics is essential for various research felds, among them climate and its interaction with the land surface. SSM dynamics is mainly driven by precipitation but also by evapotranspiration, infltration and drainage to deeper layers. Soil types, land cover and vegetation characteristics have signifcant influence on the last mentioned three drivers.Soil moisture can signifcantly affect the atmospheric variability through changes in the partition between latent and sensible energy fluxes on time scales ranging from diurnal to seasonal, in particular over transition regions between wet and dry climates. Several studies that employed climate models and Land Surface Models (LSMs) (Sörensson and Menéndez, 2011; Ruscica et al., 2015; Spennemann and Saulo, 2015; Ruscica et al., 2016) and more recently satellite products (Salvia et al., 2016, Spennemann et al., 2017, submitted) distinguish southeastern South America (SESA) as a hotspot of land-atmosphere interaction during austral summer.Regarding the behavior of SSM satellite derived products in the area, a recent work by Grings et al. (2015) over the Pampas Plains in SESA shows characteristic soil moisture patterns that follow the standardized precipitation index under extreme wet and dry conditions using the GLDAS Noah-LSM, ASCAT and SMOS satellite products, and in-situ measurements from the soil moisture network established by CONAE?s Space Center in Argentina.The aim of this work is to achieve a deeper understanding of SSM dynamics over the SESA hotspot area during austral summer. The ORCHIDEE LSM (http://labex.ipsl.fr/orchidee/) and the more recent version of SMOS satellite product (v.620) are chosen for this study. ORCHIDEE provides a high vertical resolution of the soil surface, making it suitable for comparison with remote sensing products. For example, ORCHIDEE represents the 35 upper mm with 4 layers, compared to other frequently used LSMs as Noah that represents the 100 upper mm with 1 layer. SMOS v.620 includes a new parameterization for forested areas that reduces uncertainties as well as improvements in L1 and data quality fltering (https://earth.esa.int/documents/10174/1854503/SMOS_L2SMv620_release_note).The SSM dynamics is explored using 3-hourly data from ORCHIDEE and the SMOS L2 soil moisture product, which provides total coverage over the area every 1-2 days. The spatial resolution of both datasets is 25 km. Temporal e-folding decay of SSM during non-rainy days after a marked precipitation event is explored through composites for both datasets for the summers between2010 and 2014. Results are analyzed in terms of soil and land cover characteristics, sampling frequency and precipitation uncertainties. A specifc measurement of SSM dynamics (Mc Coll et al., 2017) is also calculated for a more complete description of the SSM behavior in the area.