Verónica González-Gambau

A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula

The ESAs Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite devoted to measure the Earths surface soil moisture. It has a spatial resolution of ~ 40 km and a 3-day revisit. In this paper, a downscaling algorithm is presented as a new ability to obtain multiresolution soil moisture estimates from SMOS using visible-to-infrared remotely sensed observations. This algorithm is applied to combine 2 years of SMOS and MODIS Terra/Aqua data over the Iberian Peninsula into fine-scale (1 km) soil moisture estimates. Disaggregated soil moisture maps are compared to 0-5 cm ground-based measurements from the REMEDHUS network. Three matching strategies are employed: 1) a comparison at 40 km spatial resolution is undertaken to ensure SMOS sensitivity is preserved in the downscaled maps; 2) the spatio-temporal correlation of downscaled maps is analyzed through comparison with point-scale observations; and 3) high-resolution maps and ground-based observations are aggregated per land-use to identify spatial patterns related with vegetation activity and soil type. Results show that the downscaling method improves the spatial representation of SMOS coarse soil moisture estimates while maintaining temporal correlation and root mean squared differences with ground-based measurements. The dynamic range of in situ soil moisture measurements is reproduced in the high-resolution maps, including stations with different mean soil wetness conditions. Downscaled maps capture the soil moisture dynamics of general land uses, with the exception of irrigated crops. This evaluation study supports the use of this downscaling approach to enhance the spatial resolution of SMOS observations over semi-arid regions such as the Iberian Peninsula.

MIRAS Calibration and Performance: Results From the SMOS In-Orbit Commissioning Phase

After the successful launching of the Soil Moisture and Ocean Salinity satellite in November 2009, continuous streams of data started to be regularly downloaded and made available to be processed. The first six months of operation were fully dedicated to the In-Orbit Commissioning Phase, with an intense activity aimed at bringing the satellite and instrument into a fully operational condition. Concerning the payload Microwave Imaging Radiometer with Aperture Synthesis, it was fully characterized using specific orbits dedicated to check all instrument modes. The procedures, already defined during the on-ground characterization, were repeated so as to obtain realistic temperature characterization and updated internal calibration parameters. External calibration maneuvers were tested for the first time and provided absolute instrument calibration, as well as corrections to internal calibration data. Overall, performance parameters, such as stability, radiometric sensitivity and radiometric accuracy were evaluated. The main results of this activity are presented in this paper, showing that the instrument delivers stable and well-calibrated data thanks to the combination of external and internal calibration and to an accurate thermal characterization. Finally, the quality of the visibility calibration is demonstrated by producing brightness temperature images in the alias-free field of view using standard inversion techniques. Images of ocean, ice, and land are given as examples.

On-Ground Characterization of the SMOS Payload

The on-ground characterization of the synthetic aperture radiometer onboard the Soil Moisture and Ocean Salinity mission is described. Characterization includes basic functionality, internal calibration, thermal cycling, response to point and flat sources, self-radio-frequency interference, and others. The description of the different tests performed as well as the detailed results are provided. The results show that the instrument is very stable and has all gains and offsets consistent with the ones obtained at subsystem level. On the other hand, the phase of the visibility has a larger variation with temperature than expected, a small signal leakage from the local oscillators is present, and a small interference from the X-band transmitter during short periods of time has been detected. The implementation of internal-calibration procedures, along with the accurate thermal characterization performed, have been used to produce highly accurate brightness-temperature values well within specifications.

High Angular Resolution RFI Localization in Synthetic Aperture Interferometric Radiometers Using Direction-of-Arrival Estimation

Radio-frequency interference (RFI) seriously affects the retrieval of geophysical parameters from the measurements of microwave radiometers. An accurate geolocation of the RFI is crucial to effectively switch off illegal transmitters. In this letter, a new RFI localization method is proposed to improve the achievable angular resolution by using beamforming and direction-of-arrival (DOA) estimation techniques. The proposed RFI localization techniques can be employed in synthetic aperture interferometric radiometers, such as the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. Two DOA estimation techniques are tested for the RFI localization: Capon and MUSIC. The feasibility of these methods is demonstrated with SMOS data. In the test results, the MUSIC beamforming shows a better performance of RFI localization than the SMOS Fourier imaging and the Capon, in terms of accuracy and resolution.

SMOS and Aquarius Radiometers: Inter-Comparison Over Selected Targets

Passive microwave remote sensing at L-band is considered to be the most suitable technique to measure soil moisture and ocean salinity. These two variables are needed as inputs of predictive models, to improve climate and weather forecast, and to increase our knowledge of the water cycle. Nowadays, there are two space missions providing frequent and global observations of moisture and salinity of the Earths surface with L-band radiometers on-board. The first one is the ESAs SMOS satellite, launched on November 2, 2009, which carries a two-dimensional, multi-angular, and full-polarimetric synthetic aperture radiometer. The second one is the NASA/CONAEs Aquarius/SAC-D mission, launched on June 10, 2011, which includes three beam push-broom real aperture radiometers. The objective of this work is to compare SMOS and Aquarius brightness temperatures and verify the continuity and consistency of the data over the entire dynamic range of observations. This is paramount if data from both radiometers are used for any long term enviromental, meteorological, hydrological, or climatological studies. The inter-comparison approach proposed is based on the study of 1 year of measurements over key target regions selected as representative of land, ice, and sea surfaces. The level of linearity, the correlation, and the differences between the observations of the two radiometers are analyzed. Results show a higher linear correlation between SMOS and Aquarius brightness temperatures over land than over sea. A seasonal effect and spatial inhomogeneities are observed over ice, at the Dome-C region. In all targets, better agreement is found in horizontal than in vertical polarization. Also, the correlation is higher at higher incidence angles. These differences indicate that there is a non-linear effect between the two instruments, not only a bias.

On the synergy of SMOS and Terra/Aqua MODIS: High resolution soil moisture maps in near real-time

An innovative downscaling approach to obtain fine-scale soil moisture estimates from 40 km SMOS observations has been developed. It optimally blends SMOS multi-angular and full-polarimetric information with MODIS visible/data into high resolution soil moisture maps. The core of the algorithm is a model that linksmicrowave/optical sensitivity to soilmoisture and linearly relates the two instruments across spatial scales. This algorithm has been implemented at SMOS-BEC facilities and near real-time maps of disaggregated soil moisture over the Iberian Peninsula are being distributed. In this work, the temporal and spatial variability of these maps is evaluated through comparison with ground-basedmesurements acquired at the REMEDHUS soil moisture network, in the central part of the Duero basin, Spain. Results from a two-year time-series comparison show that downscaled soil moisture maps compare well with in situ data and nicely reproduce soil moisture dynamics at a 1 km spatial scale.

Improved MUSIC-Based SMOS RFI Source Detection and Geolocation Algorithm

The European Space Agencys Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, and multiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.

Nodal Sampling: A New Image Reconstruction Algorithm for SMOS

Soil moisture and ocean salinity (SMOS) brightness temperature (TB) images and calibrated visibilities are related by the so-called G-matrix. Due to the incomplete sampling at some spatial frequencies, sharp transitions in the TB scenes generate a Gibbs-like contamination ringing and spread sidelobes. In the current SMOS image reconstruction strategy, a Blackman window is applied to the Fourier components of the TBs to diminish the amplitude of artifacts such as ripples, as well as other Gibbs-like effects. In this paper, a novel image reconstruction algorithm focused on the reduction of Gibbs-like contamination in TB images is proposed. It is based on sampling the TB images at the nodal points, that is, at those points at which the oscillating interference causes the minimum distortion to the geophysical signal. Results show a significant reduction of ripples and sidelobes in strongly radio-frequency interference contaminated images. This technique has been thoroughly validated using snapshots over the ocean, by comparing TBs reconstructed in the standard way or using the nodal sampling (NS) with modeled TBs. Tests have revealed that the standard deviation of the difference between the measurement and the model is reduced around 1 K over clean and stable zones when using NS technique with respect to the SMOS image reconstruction baseline. The reduction is approximately 0.7 K when considering the global ocean. This represents a crucial improvement in TB quality, which will translate in an enhancement of the retrieved geophysical parameters, particularly the sea surface salinity.

First results on MIRAS calibration and overall SMOS performance

After the successful launching of the SMOS satellite, the first continuous streams of data are being processed and carefully analyzed in the frame of the SMOS In-Orbit Commissioning phase. Results regarding instrument calibration parameters retrieval, both internal and external, and brightness temperature imaging are presented. Images of ocean, ice and land are given as examples.

The MIRAS “all-licef” calibration mode

Since each of the individual elements of the MIRAS array is a total power radiometer, the zero-spacing visibility can be obtained by the average of all the corresponding antenna temperatures. The main advantage of this option with respect to using the NIR measurements is that amplitude calibration is more consistent between zero-spacing visibility and the rest. On the other hand, total power radiometers are not usually as stable as noise injection radiometers, so a small loose of stability could be expected. Preliminary results show, however, similar performance.