Assessment of Multi-Scale SMOS and SMAP Soil Moisture Products across the Iberian Peninsula

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. Keywords: soil moisture; moisture variability; temporal dynamics; moisture patterns; spatial disaggregation; Soil Moisture Active Passive (SMAP); Soil Moisure and Ocean Salinity (SMOS); REMEDHUSSobre la continuidad de las misiones satelitales debanda L. Nuevos paradigmas en productos y aplicaciones, grant numbers ESP2017-89463-C3-2-R (UPC part) andESP2017-89463-C3-1-R (ICM part)Unidad de Excelencia María de Maeztu MDM-2016-060

Incidence Angle Diversity on L-Band Microwave Radiometry and its Impact on Consistent Soil Moisture Retrievals

Incidence angle diversity of space-borne L-band radiometers needs to be taken into account for a consistent estimation of surface soil moisture (SM). In this study, the Land Parameter Retrieval Model (LPRM) is applied to SMOS brightness temperatures to calibrate the effective scattering albedo (w) and the soil roughness (h 1 ) parameter against ERA5-land SM. The analysis is carried out for SMOS data at three different incidence angles ( 32.5±5∘, 42.5±5∘ and 52.5±5∘ ) focusing in 2016 on the three main land cover types of the Iberian Peninsula according to the Climate Change Initiative (agricultural, forest and grassland). The parameterization shows an increasing trend of w and h 1 with rise of incidence angle. The SM retrieval have been evaluated with in situ SM measurements of the REMEDHUS network on rainfed crop fields. Both compare well at the three incidence angles, obtaining high correlations (0.81-0.85), an ubRMSE around 0.04 m 3 m −3 and low bias (0-0.015 m 3 m −3)With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

Investigations on High-Resolution Soil Moisture Maps from Microwave-Based Multi-Sensor Approaches

European Space Agency’s 2019 Living Planet Symposium, 13-17 May 2019, Milan, ItalySoil moisture is an essential climate variable which plays a crucial role linking the Earth’s water, energy and carbon cycles between the land and the atmosphere. Although it represents a small percentage of all the water on Earth, it provides key information about evaporation, transpiration, infiltration and runoff. As a result, accurate knowledge of soil moisture is crucial for both global and local applications. Currently there are two operating missions, SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active and Passive), launched by ESA and NASA, which are specifically devoted to measure the (surface) soil moisture. Their passive microwave instruments operate at L-band, which is favorable for measuring soil moisture due to the high sensitivity of the microwave signal to the soil dielectric constant at this frequency. The Copernicus Imaging Microwave Radiometer (CIMR) high priority candidate mission is planned to have an L-band radiometer on-board and could provide continuation of the observational data stream. Accurate high-resolution soil moisture maps are needed to fulfill a growing number of application tasks e.g., prevention of wildfires [1][2], early-detection of forest decline [3], monitoring the evolution of insect pests [4]. To downscale soil moisture from the coarse-scale radiometer resolution to a finer one, downscaling algorithms typically use additional observations at fine scales. A wide variety of downscaling algorithms exists [5]. They may use observations from different sensors, use different ancillary data or rely on different physical assumptions. The performance of these algorithms depends on the physics they are based on, and on the information at fine scale that they use, which may also depend on season, climate and land cover. This makes a direct comparison difficult, since their performance is intrinsically time and region dependent, and the algorithm set-up will therefore reflect into the results. The baseline downscaling approach for the SMAP mission uses active and passive microwaves. SMAP was designed to have a radar and a radiometer on-board, but the radar stopped operating on July 7, 2015. An alternative active-passive soil moisture product is now available merging SMAP and Sentinel-1 data [6]. Recently a spatially-consistent downscaling algorithm has been developed to obtain high-resolution soil moisture maps at 1 km from the ~30-40 km native resolution of current passive microwave instruments using optical data. This algorithm is based on the semi-empirical downscaling approach implemented at the Barcelona Expert Center (BEC) to blend SMOS and MODIS data into 1 km soil moisture estimates [7]. The novelty is that it introduces the concept of a shape adaptive window, improving its spatial consistency and thereby allowing for its global implementation [8]. The objective of this study is to provide insight into the physical mechanisms that can influence the production (downscaling) of high-resolution soil moisture maps with a special focus on soil moisture anomalies. We will investigate soil moisture maps produced by the BEC (microwave-optical) and the SMAP-Sentinel (active-passive microwave) algorithms presented above and understand the characteristics of the downscaled soil moisture maps with a focus on spatial and temporal anomalies.[1] D. Chaparro, M. Piles, M. Vall-Llossera, A. Camps, “Surface moisture and temperature trends anticipate drought conditions linked to wildfire activity in the Iberian Peninsula,” European Journal of Remote Sensing, vol. 49, issue 1, pp. 955-971, 2016. [2] D. Chaparro, M. Vall-llossera, M. Piles, A. Camps, C. Rüdiger and R. Riera-Tatché, "Predicting the Extent of Wildfires Using Remotely Sensed Soil Moisture and Temperature Trends," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 6, pp. 2818-2829, June 2016. [3] D. Chaparro, J. Vayreda, M. Vall-llossera, M. Banqué, M. Piles, A. Camps, J. Martínez-Vilalta, “The role of climatic anomalies and soil moisture in the decline of drought-prone forests,”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, issue 2, pp. 503-514, 2017. [4] M. J. Escorihuela, O. Merlin, V. Stefan, G. Moyano, O. A. Eweys, M. Zribi, ... & S. Ghaout. “SMOS based high resolution soil moisture estimates for Desert locust preventive. [5] J. Peng, A. Loew, O. Merlin, N. Verhoest, “A review of spatial downscaling of satellite remotely sensed soil moisture,” Reviews of Geophysics, 10.1002/2016RG000543, March 2017. [6] N. Das, R.S. Dunbar, “Level 2 SMAP/Sentinel Active/Passive Soil Moisture Product Specification Document,” Jet Propulsion Laboratory, D-56548, August 2017. [7] M. Piles, N. Sánchez, M. Vall-llossera, A. Camps, J. Martínez-Fernández, J. Martínez, V. González-Gambau, “A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula,” IEEE Journal of Sel. Topics in Applied Earth Obs. and Remote Sens., vol. 7, no. 9, pp. 3845-3857, 2014. [8] G. Portal et al., "A Spatially Consistent Downscaling Approach for SMOS Using an Adaptive Moving Window," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 6, pp. 1883-1894, June 2018Peer reviewe