Comparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula

Abstract

The aim of this study is to compare the surface soil moisture (SSM) retrieved from ESA's Soil Moisture and Ocean Salinity mission (SMOS) with the output of the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEm) land surface model forced with two distinct atmospheric data sets for the period 2010 to 2012. The comparison methodology is first established over the REMEDHUS (Red de Estaciones de MEDición de la Humedad def Suelo) soil moisture measurement network, a 30 by 40. km catchment located in the central part of the Duero basin, then extended to the whole Iberian Peninsula (IP). The temporal correlation between the in-situ, remotely sensed and modelled SSM are satisfactory (r. >. 0.8). The correlation between remotely sensed and modelled SSM also holds when computed over the IP. Still, by using spectral analysis techniques, important disagreements in the effective inertia of the corresponding moisture reservoir are found. This is reflected in the spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates, which is poor (¿. ~. 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products.Peer ReviewedPostprint (published version

Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

“…This study follows the comparison between modelled and retrieved SSM (Polcher et al, 2016) and attempts to elucidate whether the difference found can be attributed either to the retrieval algorithm, which converts TBs into estimated SSM, or its modelled counterpart.…”

“…For instance, Polcher et al (2016) show that temporal correlation measured between remotely sensed, in situ, and modelled SSM is mainly driven by the high-frequency behaviour of SSM. Therefore, this diagnostic is not very sensitive to the slower variations of the field studied.…”

“…Values from the SSM comparison performed by Polcher et al (2016) are also included. The differences between spatial and temporal correlations are already apparent and warrant separate analyses as a first step.…”

“…It provides information regarding the origin of their differences and whether they are due to the retrieval algorithm or to issues related to the modelling process. Polcher et al (2016) present the first comparison of the spatial patterns of the Level 2 (L2) SMOS product corresponding to retrieved SSM, with SSM modelled by the ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) LSM (de Rosnay and Polcher, 1998;Krinner et al, 2005) over the Iberian Peninsula (IP) from 2010 to 2013. They identify inconsistencies between the spatial structures of retrieved and modelled SSM.…”

“…The RTM used is the Community Microwave Emission Model (CMEM) (de Rosnay et al, 2009), developed by the European Centre for MediumRange Weather Forecasts (ECMWF). The comparison is performed over the same period and region as the study carried out by Polcher et al (2016). The IP is an excellent test case for remote sensing of SSM, as its two characteristic climate regimes (oceanic and Mediterranean) result in a strong contrast in soil water content.…”