Evaluation of the Soil Moisture Operational Estimates From SMOS in Europe: Results Over Diverse Ecosystems

Abstract

This study presents the results of an extensive validation of the Soil Moisture and Ocean Salinity mission (SMOS) soil moisture operational product from selected European sites representative of a variety of climatic, environmental, biome, and seasonal conditions. SMOS soil moisture estimates were compared against corresponding in-situ measurements from the CarboEurope observational network. The agreement between the two datasets was evaluated on the basis of a series of statistical metrics. In addition, the effect of variability of site characteristics such as land cover, seasonality, and also that of the Radio Frequency Interference (RFI) effect on SMOS was explored. In overall, the SMOS soil moisture product estimates agreed reasonably well with near concurrent CarboEurope in-situ measurements acquired from the 0-5 cm soil moisture layer. Significant changes in the SMOS performance were observed with local adjustments, such as land cover and seasonal changes. Agreement was found to be higher over low vegetation cover and during the autumn season. The RFI contaminated pixels were filtered out from the pooled datasets, as well as from the seasonally discriminated datasets, which resulted in noticeably improved performances. This paper provides strong supportive evidence of the potential value of the SMOS soil moisture product for hydrometeorological and related studies.

Operational Soil Moisture from ASCAT in Support of Water Resources Management

“…Satellite soil moisture was acquired from the ASCAT sensor, onboard the MetOp satellite platform. ASCAT is a microwave real aperture radar sensor that measures the radar backscatter at C-band in a vertical Polarization [31]. Measurements are taken on both sides of the sub-satellite track over two 550 km wide swaths, from an 817 km height orbit; there are 14 orbit revolutions per day, resulting in a global coverage being achieved in~1.5 days.…”

“…Backscatter measurements from this sensor are transformed into SSM estimates with the TU Wien method that was originally developed for the ERS AMI WS instruments by Wagner et al [42] and improved by Naeimi et al [43]. EUMETSAT provides this operational dataset in near real time [31] and the Vienna University of Technology, Austria provides it as a reprocessed archive. It has a spatial resolution of 25 km grids and it is produced by a means of the TU Wien algorithm.…”

“…It includes two aspects: one is that the result of the validation can be used as a feedback to algorithm developers for further improvements in the retrieval of SSM; the other is to facilitate the potential users to understand the status of the product, such as the accuracy, magnitude, and the uncertainties of the remote sensed products. Both are very important as they help in better understanding their potential use for practical applications (e.g., [20,31]). Additionally, long term soil moisture datasets are been used in hydrological and land surface modeling assimilation [26,32].…”

Validation and Upscaling of Soil Moisture Satellite Products in Romania

“…There are a important number of papers that deals with MOS validation for the entire world (Clément Albergel et al, 2011;Al-Yaari, Wigneron, Ducharne, Kerr, Wagner, et al, 2014;Louvet et al, 2015;Pan et al, 2012;Petropoulos, Ireland, & Barrett, 2015;Petropoulos, Ireland, & Srivastava, 2015;Pierdicca et al, 2015;Scaini, Sanchez, Vicente-Serrano, & Martinez-Fernandez, 2015;Wanders et al, 2012). Most of the papers are assessing the SMOS soil moisture by comparison with in-situ data.…”

“…Moreover, with the changing climate there is a need for long term spatially distributed soil moisture data. Spaceborne microwave remote sensing has proven to be a valuable tool to fulfil those needs by quantitatively measuring soil moisture on a global scale under a variety of conditions (Clement Albergel et al, 2012;Clément Albergel et al, 2011;Dorigo et al, 2015;Draper et al, 2013;Louvet et al, 2015;Panciera et al, 2009;Petropoulos, Ireland, & Barrett, 2015;Petropoulos, Ireland, & Srivastava, 2015;Pierdicca et al, 2015;Piles, Petropoulos, Sánchez, González-Zamora, & Ireland, 2016;Rossato, De Jeu, Alvalá, & Souza, 2011) It monitors soil moisture on a spatial and temporal scale, which cannot be achieved with in situ sampling. However, soil moisture is highly variable in both space and time as a result of heterogeneity in vegetation, soil properties, topography and climatic drivers.…”