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Changes in the Earth's water cycle can be estimated by analyzing sea surface salinity. This variable reflects the balance between precipitation and evaporation over the ocean, since the upper layers of the ocean are the most sensitive to atmosphere–ocean interactions. In situ measurements lack spatial and temporal synopticity and are typically acquired at few meters below the surface. Satellite measurements, on the contrary, are synoptic, repetitive and acquired at the surface. Here we show that the satellite-derived sea surface salinity measurements evidence an intensification of the water cycle (the freshest waters become fresher and vice-versa) which is not observed at the in-situ near-surface salinity measurements. The largest positive differences between surface and near-surface salinity trends are located over regions characterized by a decrease in the mixed layer depth and the sea surface wind speed, and an increase in sea surface temperature, which is consistent with an increased stratification of the water column due to global warming. These results highlight the crucial importance of using satellites to unveil critical changes on ocean–atmosphere fluxes. [ABSTRACT FROM AUTHOR]

The microwave imaging radiometer with aperture synthesis (MIRAS) is formed by 69 total power radiometers, of which three are the noise-injection type. Their calibration is reviewed on the basis of the data gathered during more than eight years of operation. Internally calibrated gain and offset corrections with improved temporal stability are presented. New front-end loss characterization with lower seasonal dependence originated from external temperature swings is also proposed. Finally, a methodology to validate the external calibrations, with the instrument pointing to the cold sky, is developed. It seems to indicate that the change of orientation of the instrument, with associated thermal variations, may induce small changes in the radiometer front-end losses, thus introducing calibration errors. [ABSTRACT FROM AUTHOR]

A method for internally calibrating microwave total power radiometers by using only one level of noise injection is presented. It is based on having a previous accurate characterization of the receiver noise temperature, which used de facto as a second calibration standard. The method proves to be at least equivalent to the classical two level, as demonstrated through their intercomparison using the data provided by the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) on board the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Satellite. The long-term stability in terms of retrieved brightness temperature using both methods has similar trends with a small advantage for the one-point approach proposed here. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Land–sea contamination observed in Soil Moisture and Ocean Salinity (SMOS) brightness temperature images is found to have two main contributions: the floor error inherent of image reconstruction and a multiplicative error either in the antenna temperature or in the visibility samples measured by the correlator. The origin of this last one is traced down to SMOS calibration parameters to yield a simple correction scheme, which is validated against several geophysical scenarios. Autoconsistency rules in interferometric synthesis together with redundant and complementary calibration procedures provide a robust SMOS calibration scheme. [ABSTRACT FROM PUBLISHER]

Faraday rotation is dynamically computed from L-band radiometric data acquired by the Soil Moisture and Ocean Salinity satellite. Improved full polarimetric image reconstruction and smart spatiotemporal filtering are used to obtain good estimations of Faraday rotation, which compare very well with the values theoretically predicted from available ionosphere and geomagnetic field data. [ABSTRACT FROM PUBLISHER]

This work has been conducted in the framework of several projects devoted to assess the performance of the Soil Moisture and Ocean Salinity (SMOS) mission full-pol measurement mode. Since its launch in November 2009, SMOS is producing dual-polarization brightness temperature synthesized images that are yielding a high scientific return. However, these images are affected by a non-negligible spatial amplitude error, the so-called spatial bias (SB), that degrades geophysical parameter retrieval. This effect is particularly detrimental in SMOS polarimetric images where spatial bias is masking the polarimetric physical signature to a large extend. This paper presents a method to mitigate SMOS spatial bias by taking into account the co- and cross-polar antenna patterns in the image reconstruction algorithm through the, so called, full-pol G-matrix (FPG). The method is validated by producing spatial bias maps out of the comparison between SMOS full-pol images and an accurate polarimetric brightness temperature model of the ocean. This model has been provided to SMOS ESLs (Expert Support Laboratories) by LOCEAN (Laboratoire d'Océanographie et du Climat, France) as a test bench to validate and improve SMOS Level 1 (L1) data. Finally, a radiometric performance summary table comparing spatial bias and radiometric sensitivity between this new FPG approach and SMOS current co-polar G-matrix approach (CPG) is provided. This paper presents the best quality SMOS polarimetric images, which may lead a breakthrough in the science returns of the mission. [ABSTRACT FROM PUBLISHER]

The local oscillators (LOs) of the Soil Moisture and Ocean Salinity mission payload are used to shift the operating frequency of the 72 receivers to an optimal intermediate frequency needed for the signal processing. The LO temperature variations produce phase errors in the visibility, which result in a blurring of the reconstructed brightness temperature (Tb) image. At the end of the commissioning phase, it was decided to calibrate the LO every 10 min while waiting for a more in-depth analysis. During short periods of time, the LO calibration has been performed every 2 min to assess the impact of a higher calibration rate on the quality of the data. In this paper, by means of a decimation experiment, the relative errors of 6- and 10-min calibration interval data sets are estimated using the 2 min as a reference. A noticeable systematic across- and along-track pattern of amplitude \pm0.3 K is observed for Tb differences between 10 and 2 min, whereas this is reduced between 6 and 2 min. A simulation experiment confirms that the nature of such systematic pattern is due to the visibility phase errors induced by the LO calibration rate. Such pattern is propagated into the sea surface salinity (SSS) retrievals. Overall, the SSS error increase (relative to the 2 min SSS data) is about 0.39 and 0.14 psu for the 10- and 6-min data sets, respectively. This paper shows that a LO calibration rate of at least 6 min would noticeably improve the SSS retrievals. [ABSTRACT FROM AUTHOR]

The Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) on-board the Soil Moisture and Ocean Salinity (SMOS) mission is providing useful data since November 2009, and proving the potential of 2D interferometry from space. With the end of its nominal operation phase in November 2012, the mission is expected to extend its lifetime for at least more than two additional years. Along with all the current improvements on data processing and exploitation, the SMOS trail might need to be continued with the aim of providing data to the users in the coming years. This paper presents a SMOS follow-on operational mission which is the result of integrating the actual lessons learnt from MIRAS with a novel hexagonal array geometry, proving robustness against radio-frequency interferences (RFI) and receiver failures. The performance and the instrument architecture enhancements are exposed, along with a practical deployment solution. [ABSTRACT FROM PUBLISHER]

This work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoring. [ABSTRACT FROM AUTHOR]

Soil Moisture and Ocean Salinity (SMOS) brightness temperature synthesized images are obtained after a comprehensive error correction procedure that takes into account both on-ground and in-flight calibration measurements. However, the final images are still contaminated by small, although nonnegligible, spatial errors: the so-called pixel bias. Since spatial errors in the 2-D SMOS images are not zero mean along track, these errors produce clearly visible artifacts aligned to this direction. Fortunately, spatial errors have been found to be very stable and can be minimized once the image distortion pattern is properly measured by observing a target at a uniform brightness temperature distribution. This letter describes the procedure to compute a multiplicative mask that largely reduces spatial errors over the ocean. Preliminary results to assess the mask performance are also presented by computing the reduction of the rms spatial error for a number of targets selected to have significant temporal and geographical diversity. [ABSTRACT FROM PUBLISHER]

A downscaling approach to improve the spatial resolution of Soil Moisture and Ocean Salinity (SMOS) soil moisture estimates with the use of higher resolution visible/infrared (VIS/IR) satellite data is presented. The algorithm is based on the so-called “universal triangle” concept that relates VIS/IR parameters, such as the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (Ts), to the soil moisture status. It combines the accuracy of SMOS observations with the high spatial resolution of VIS/IR satellite data into accurate soil moisture estimates at high spatial resolution. In preparation for the SMOS launch, the algorithm was tested using observations of the UPC Airborne RadIomEter at L-band (ARIEL) over the Soil Moisture Measurement Network of the University of Salamanca (REMEDHUS) in Zamora (Spain), and LANDSAT imagery. Results showed fairly good agreement with ground-based soil moisture measurements and illustrated the strength of the link between VIS/IR satellite data and soil moisture status. Following the SMOS launch, a downscaling strategy for the estimation of soil moisture at high resolution from SMOS using MODIS VIS/IR data has been developed. The method has been applied to some of the first SMOS images acquired during the commissioning phase and is validated against in situ soil moisture data from the OZnet soil moisture monitoring network, in South-Eastern Australia. Results show that the soil moisture variability is effectively captured at 10 and 1 km spatial scales without a significant degradation of the root mean square error. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents a general analysis of correlation measurements in an interferometer or a radiometer based on noise injection and/or switching and measurement of normalized correlations (e.g., imaging synthetic aperture or polarimetric radiometers). A compact unifying notation for denormalizing the measured normalized correlations in the presence of noise injection in one or both of the receiving channels is presented. Technological limitations are also assessed by evaluating the effect of associated approximations. Finally, the approach is validated by experimental results of the measurement and calibration of related front-end nonidealities, namely, the finite isolation of the front-end switch. The methods presented in this paper are illustrated by a thorough analysis of the so-called mixed baselines of microwave imaging radiometer using aperture synthesis, which refer to those baselines which are formed between the regular receivers (light-weight cost-efficient front-end) and the reference radiometers. These baselines require special attention, since the reference radiometers are noise-injection radiometers, which inject noise to the measured signal, whereas the regular receivers are total power receivers. [ABSTRACT FROM AUTHOR]

Brightness-temperature retrieval techniques for synthetic aperture radiometers are reviewed. Three different approaches to combine measured visibility and antenna temperatures, along with instrument characterization data, into a general equation to invert are presented. Discretization and windowing techniques are briefly discussed, and formulas for reciprocal grids using rectangular and hexagonal samplings are given. Two known techniques are used to invert the equation, namely, inverse Fourier transform and G -matrix pseudoinverse. The proposed preprocessing approaches combined with these two inversion methods are implemented with real data measured by an airborne Y-shaped interferometric radiometer over land and water, and are compared. The images indicate that best results are obtained when inverting an incremental visibility obtained after substracting a term that includes the individual antenna temperatures, the physical temperatures of the receivers, and a flat-target response directly measured from cold-sky looks. [ABSTRACT FROM PUBLISHER]

This paper describes AMIRAS, an airborne demonstrator of the Microwave Imaging Radiometer with Aperture Synthesis, which is the instrument onboard ESA's Soil Moisture and Ocean Salinity (SMOS) mission. The main electrical, mechanical, thermal, and control elements of the demonstrator are shown, together with its capabilities and performances as demonstrator of the spaceborne instrument. AMIRAS main tests inside an anechoic chamber, field ground experiments, and its first two maiden flights are reported, and some results of these tests are highlighted. AMIRAS will further be used in some calibration and validation campaigns of the SMOS mission. [ABSTRACT FROM AUTHOR]

The calibration of the Soil Moisture and Ocean Salinity (SMOS) payload instrument, known as Microwave Imaging Radiometer by Aperture Synthesis (MIRAS), is based on characterization measurements which are performed initially on-ground prior to launch and, subsequently, in-flight. A good calibration is a prerequisite to ensure the quality of the geophysical data. The calibration scheme encompasses both the spaceborne instrument and the ground data processing. Once the system has been calibrated, the instrument performance can be verified, and the higher level geophysical variables, soil moisture and ocean salinity, can be validated. In this paper, the overall calibration approach is presented, focusing on the main aspects relevant to the SMOS instrument design and mission requirements. The distributed instrument, comprising 72 receivers, leads to a distributed internal calibration approach supported by specific external calibration measurements. The relationship between the calibration data and the routine ground processing is summarized, demonstrating the inherent link between them. Finally, the approach to the in-flight commissioning activities is discussed. [ABSTRACT FROM AUTHOR]

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission aims at producing global and frequent maps of SMOS and will be launched in 2008. SMOS' single payload is a new type of radiometer called Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) operating at L-band in which brightness temperature images are formed by a Fourier synthesis technique. However, in the alias-free field of view where the brightness temperature images are reconstructed, a bias is present which has been found to be higher for high- contrast brightness temperature scenes (coastlines) and lower for homogeneous scenes (all oceans or lands). This scene-dependent bias will ultimately limit the achievable accuracy of the retrieved geophysical parameters, and it is particularly critical for the retrieval of sea surface salinity. This paper presents a general analysis of the origin of this bias, which is found to be actually due to the different measurement errors in the instrument observables (visibility samples). An improvement of the image reconstruction algorithm is then presented to mitigate it. As compared with the previous algorithm versions, the proposed improved reconstruction algorithm further decomposes the visibility samples into some new terms: ocean and land/iced sea, instead of just the Earth's disk over the sky background. This decomposition aims at further reducing the contrast (high-frequency components) in the differential image and, therefore, minimizes the impact of multiplicative errors, improving the radiometric accuracy. In addition, this approach proves to perform the image reconstruction in part of the alias regions and improves the quality of the reconstruction close to the coastlines. [ABSTRACT FROM AUTHOR]

This paper reviews the relative calibration of an interferometric radiometer taking into account the experimental results of the first batch of receivers developed in the frame of the European Space Agency's Soil Moisture and Ocean Salinity mission. Measurements show state-of-the-art baseline performance as long as the system is capable of correcting the effect of orbital temperature swing. A method to validate internal calibration during in-orbit deep-sky views and to correct linearity errors is also presented. [ABSTRACT FROM AUTHOR]

A complete and systematic noise analysis of radiometer front-ends, including both total power and correlation measurements, is presented. The procedure uses the concepts of noise waves and S-parameters, widely used in microwave systems design and takes into account full noise characterization of receivers including mismatch effects. The general formulation is compatible with known total power radiometer analysis and is specially appropriate in correlation radiometers for which the effect of nonideal components, such as input isolators, is analyzed. Along with numerical simulations, simple formulas are given to compute the measured visibility in nonideal conditions. The analysis is validated using experimental results consisting of correlation measurements of four receivers placed inside an anechoic chamber. Good agreement between theoretical predictions and experimental data is observed. [ABSTRACT FROM AUTHOR]

The Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission was selected hi May 1999 by the European Space Agency Earth Observation Programme Board to provide global, and frequent soil moisture (SM) and sea surface salinity (SSS) maps. SMOS' single payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) sensor, an L-band two-dimensional aperture synthesis interferometric radiometer with multiangular and polarlimetric imaging capabilities. The definition of the SMOS Level 2 Processor requires the selection of the. optimum operation mode (dual-polarization or full-polarimetric) for each application, the specification of the required auxiliary data, and the optimum retrieval algorithms. Using the SMOS simulator and based on the experience gained in previous works this paper presents a study of the SM and SSS retrieval capabilities overhomogeneous pixels, in the two modes of operation with different auxiliary data. It is found that 555 retrievals using the first Stokes parameter measured in the dual-polarization mode perform somewhat worse than using the vertical (Tvv) and horizontal (Thh) brightness temperatures measured in the full-polarimetric mode, and the performance degrades for cold waters due to the lower sensitivity of the brightness temperature to SSS at low sea surface temperature (SST). Due to the larger angular variation of Thh and Tvv, SM retrievals using Thh and Tvv measured in the full-polarlmetric mode exhibit a significant better performance over bare soils than over vegetation-covered soils. Over vegetation-covered soils vegetation parameters (opacity and albedo) can be inferred over a 550-km swath width In the full-polarimetric mode. However, since the first Stokes parameter is independent of both geometric and Faraday rotations, it is very robust in the presence of instrumental and geophysical errors. In the SSS retrieval problem and in the SM retrieval problem (with Thh and Tvv measured in the full-polarimetric mode), the performance of the retrieval algorithms tested is not significantly altered if the model parameters are not exactly known, but are left as adjustable parameters in the optimization process. [ABSTRACT FROM AUTHOR]