A soil moisture and temperature network for SMOS validation in Western Denmark

The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data of global coverage every three days. Product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and soil temperature sensor network was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature and precipitation between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved soil moisture (<i>R</i><sup>2</sup> of 0.49) as well as initial soil moisture and temperature from ECMWF used in the retrieval algorithm (<i>R</i><sup>2</sup> of 0.67 and 0.97, respectively). While retrieved/initial SMOS soil moisture indicate significant under-/overestimation of the network data (biases of −0.092/0.057 m<sup>3</sup> m<sup>−3</sup>), the initial temperature is in good agreement (bias of −0.2 °C). Based on these findings, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies

SMOS calibration and validation activities with airborne interferometric radiometer HUT-2D during spring 2010

In this paper we present calibration and validation activities of European Space Agency’s SMOS mission, which utilize airborne interferomentric L-band radiometer system HUT-2D of the Aalto University. During spring 2010 the instrument was used to measure three SMOS validation target areas, one in Denmark and two in Germany. We present these areas shortly, and describe the airborne activities. We show some exemplary measurements of the radiometer system and demonstrate the studies using the data

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

The objective of this study was to compare several approaches to soil moisture (SM) retrieval using L-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30-60). Based on a three year data set (2010-2012), several SM retrieval approaches developed for spaceborne missions including AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMAP (Soil Moisture Active Passive) and SMOS were compared. The approaches include: the Single Channel Algorithm (SCA) for horizontal (SCA-H) and vertical (SCA-V) polarizations, the Dual Channel Algorithm (DCA), the Land Parameter Retrieval Model (LPRM) and two simplified approaches based on statistical regressions (referred to as 'Mattar' and 'Saleh'). Time series of vegetation indices required for three of the algorithms (SCA-H, SCA-V and Mattar) were obtained from MODIS observations. The SM retrievals were evaluated against reference SM values estimated from a multiangular 2-Parameter inversion approach. The results obtained with the current base line algorithms developed for SMAP (SCA-H and -V) are in very good agreement with the reference SM data set derived from the multi-angular observations (R2 around 0.90, RMSE varying between 0.035 and 0.056 m3m3 for several retrieval configurations). This result showed that, provided the relationship between vegetation optical depth and a remotely-sensed vegetation index can be calibrated, the SCA algorithms can provide results very close to those obtained from multi-angular observations in this study area. The approaches based on statistical regressions provided similar results and the best accuracy was obtained with the Saleh methods based on either bi-angular or bipolarization observations (R2 around 0.93, RMSE around 0.035 m3m3). The LPRM and DCA algorithms were found to be slightly less successful in retrieving the 'reference' SM time series (R2 around 0.75, RMSE around 0.055 m3m3). However, the two above approaches have the great advantage of not requiring any model calibrations previous to the SM retrievals

Electromagnetic characterization of organic-rich soils at the microwave L-band with ground-penetrating radar, radiometry and laboratory measurements

peer reviewedMicrowave remote sensing of the environment strongly relies on knowledge of the soil electrical properties. In this study, we characterized organic-rich soils using remote ground-penetrating radar (GPR) and radiometer as well as resonant cavity and waveguide reference methods. Organic-rich soil samples were collected from the HOBE (Hydrological Observatory) test site in the Skjern River Catchment (Denmark) and set up at the TERENO (Terrestrial Environmental Observatories) controlled test site in Selhausen (Germany). GPR and L-band radiometer measurements were performed above the soils during two months in order to cover a wide range of soil moisture conditions. GPR data were processed using full-wave inversion based on layered media Green's functions and radiometer data were inverted using a two-stream radiative transfer model for estimating the soil electrical properties. Results were compared to reference measurements carried out at the IMS laboratory (Laboratoire de l'Intégration du Matériau au Système, France) using two different methods, i.e., the small perturbation method with resonant cavity and the waveguide method. Relatively large differences were observed between the different estimation methods for the real part of the relative dielectric permittivity, while reasonable agreement were obtained with respect to its imaginary part. This was attributed to a higher sensitivity of the real part of the relative dielectric permittivity with respect to soil samples heterogeneities. This study provided valuable insights into the electrical characterization of organic soils to improve space-borne remote sensing data products

Validation of SMOS L1C and L2 Products and Important Parameters of the Retrieval Algorithm in the Skjern River Catchment, Western Denmark

The Soil Moisture and Ocean Salinity (SMOS) satellite with a passive L-band radiometer is dedicated to surface soil moisture monitoring. In addition to soil moisture, vegetation optical thickness NAD is retrieved (L2 product) from the acquired brightness temperatures (L1C product). The objective of this article is to present the validation work carried out in the Skjern River Catchment, Denmark. L1C/L2 data and the most sensitive parameters in the retrieval algorithm were analyzed by in situ data sets collected within one SMOS pixel (44 km diameter), including network and airborne campaign data. Consistent with worldwide findings, the retrieved soil moisture captures the precipitation dynamics well, but with too large amplitudes and a significant dry bias. The retrieved NAD exhibits too high values and day-to-day variability. A filter based on L2 criteria removed RFI affected data and improved the R2 between retrieved and in situ soil moisture from 0.49 to 0.61, while the bias remained (-0.092/-0.087 m3/m3, resp.). Likely error sources for the bias were located as (1) still present RFI, (2) potential link between low soil moisture and high NAD and/or low roughness parameter (HR), (3) 18/8% lower sand/higher clay fractions and 0.35 g/cm3 lower bulk density in SMOS algorithm than in situ, and (4) caveats in the Dobson dielectric mixing model. Substitution with the Mironov model and SMOS processor runs with site-specific input are planned. Differences in sampling depth between SMOS and in situ sensors (held responsible for too large SMOS amplitudes) and the role of organic surface layers will be investigated

Validation of SMOS Brightness Temperatures During the HOBE Airborne Campaign, Western Denmark

The Soil Moisture and Ocean Salinity (SMOS) mission delivers global surface soil moisture fields at high temporal resolution which is of major relevance for water management and climate predictions. Between April 26 and May 9, 2010, an airborne campaign with the L-band radiometer EMIRAD-2 was carried out within one SMOS pixel (44 × 44 km) in the Skjern River Catchment, Denmark. Concurrently, ground sampling was conducted within three 2×2 kmpatches (EMIRAD footprint size) of differing land cover. By means of this data set, the objective of this study is to present the validation of SMOS L1C brightness temperatures TB of the selected node. Data is stepwise compared from point via EMIRAD to SMOS scale. From ground soil moisture samples, TB's are pointwise estimated through the L-band microwave emission of the biosphere model using land cover specific model settings. These TB's are patchwise averaged and compared with EMIRAD TB's. A simple uncertainty assessment by means of a set of model runs with the most influencing parameters varied within a most likely interval results in a considerable spread of TB's (5-20 K). However, for each land cover class, a combination of parameters could be selected to bring modeled and EMIRAD data in good agreement. Thereby, replacing the Dobson dielectric mixing model with theMironov model decreases the overall RMSE from 11.5 K to 3.8 K. Similarly, EMIRAD data averaged at SMOS scale and corresponding SMOS TB's show good accordance on the single day where comparison is not prevented by strong radio-frequency interference (RFI) (May 2, avg. RMSE = 9.7 K). While the advantages of solid data sets of high spatial coverage and density throughout spatial scales for SMOS validation could be clearly demonstrated, small temporal variability in soil moisture conditions and RFI contamination throughout the campaign limited the extent of the validation work. Further attempts over longer time frames are planned by means of soil moisture network data as well as studies on the impacts of organic layers under natural vegetation and higher open water fractions at surrounding grid nodes