Abstract

In the last decade, technological advances led to the launch of two satellite missions dedicated to measure the Earth’s surface soil moisture (SSM): the ESA’s Soil Moisture and Ocean Salinity (SMOS) launched in 2009, and the NASA’s Soil Moisture Active Passive (SMAP) launched in 2015. The two satellites have an L-band microwave radiometer on-board to measure the Earth’s surface emission. These measurements (brightness temperatures TB) are then used to generate global maps of SSM every three days with a spatial resolution of about 30–40 km and a target accuracy of 0.04 m3/m3. To meet local applications needs, different approaches have been proposed to spatially disaggregate SMOS and SMAP TB or their SSM products. They rely on synergies between multi-sensor observations and are built upon different physical assumptions. In this study, temporal and spatial characteristics of six operational SSM products derived from SMOS and SMAP are assessed in order to diagnose their distinct features, and the rationale behind them. The study is focused on the Iberian Peninsula and covers the period from April 2015 to December 2017. A temporal inter-comparison analysis is carried out using in situ SSM data from the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS) to evaluate the impact of the spatial scale of the different products (1, 3, 9, 25, and 36 km), and their correspondence in terms of temporal dynamics. A spatial analysis is conducted for the whole Iberian Peninsula with emphasis on the added-value that the enhanced resolution products provide based on the microwave-optical (SMOS/ERA5/MODIS) or the active–passive microwave (SMAP/Sentinel-1) sensor fusion. Our results show overall agreement among time series of the products regardless their spatial scale when compared to in situ measurements. Still, higher spatial resolutions would be needed to capture local features such as small irrigated areas that are not dominant at the 1-km pixel scale. The degree to which spatial features are resolved by the enhanced resolution products depend on the multi-sensor synergies employed (at TB or soil moisture level), and on the nature of the fine-scale information used. The largest disparities between these products occur in forested areas, which may be related to the reduced sensitivity of high-resolution active microwave and optical data to soil properties under dense vegetation.

Highlights

  • Soil moisture (SM) is an essential climate variable (ECV) which plays a crucial role in the interplay between the Earth’s land and atmospheric processes [1]

  • Regarding the different land uses, the worst results were obtained for K13, an irrigated station, with a R of 0.46 for SMAPL2_E, 0.48 (−0.143 m3/m3) for SMAP L2 Radiometer (SMAPL2), and 0.46 (−0.183 m3/m3) for SMOS L3 SSM product (SMOSL3)

  • The unbiased root mean square error (uRMSE) of K13 is twice as high the objective accuracy of both space missions (SMOS and Soil Moisture Active Passive (SMAP)). This underperformance probably comes from the fact that irrigated land is not the most representative land use within the low-resolution SMAP/Soil Moisture and Ocean Salinity (SMOS) pixels, which is mostly covered by rainfed crops

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Summary

Introduction

Soil moisture (SM) is an essential climate variable (ECV) which plays a crucial role in the interplay between the Earth’s land and atmospheric processes [1]. It is involved in the energy flux partition into latent and sensible heat from the land to the atmosphere. Passive and active microwave sensors (radiometers and radars, respectively) are sensitive to the soil dielectric constant and allow estimation of surface soil moisture (SSM) [3]. Measurements at L-band (1–2 GHz) have a higher soil penetration depth and are less affected by soil roughness, vegetation, and atmospheric effects than at higher frequencies (e.g., C- or X-bands) [4,5]

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