The Faraday rotation (FR) is a nonnegligible effect at the L-band, which is the operation frequency of the Soil Moisture and Ocean Salinity (SMOS) mission. This effect introduces a rotation in the electromagnetic field polarization when propagating through the ionosphere that must be compensated. Recently, a methodology was developed in order to retrieve the vertical total electron content (VTEC) from SMOS radiometric data with the aim to better correct the FR effect [1] . In that work, systematic patterns in the retrieved FR angle (FRA) were detected. In this article, these systematic patterns are characterized and corrected to improve the quality of the retrieved VTEC maps. These maps can be then reused in the SMOS level 2 processor for the correction of the FRA in the mission. The impact of using the SMOS-derived VTEC maps instead of the VTEC data from global positioning system (GPS) measurements on the ocean brightness temperatures (TB) measurement has also been analyzed. Results of this analysis show that the usage of those maps allows a significant enhancement in the quality of the TB, which will lead to an improvement on salinity retrievals.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 11 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps being fully operational. This II-year long lifetime of SMOS, so far, has enabled the calibration and Level-1 processor team to improve the calibration procedures and the image reconstruction resulting in a new version of the Level-1 data processor, v724. To present the main performance features of this new version and the improvement in the calibration procedures constitute the main objective and content of this presentation.

16th Specialist Meeting on on Microwave Radiometry and Remote Sensing of the Environment, 16-20 November 2020

In this work, a new methodology is proposed in order to derive vertical total electron content (VTEC) maps from the radiometric measurements of the Soil Moisture and Ocean Salinity (SMOS) mission as an alternative approach to those based on external databases and models. This approach uses spatiotemporal filtering techniques with optimized filters to be robust against the thermal noise and image reconstruction artifacts present in SMOS images. It is also possible to retrieve the Faraday rotation angle from the recovered VTEC maps in order to correct the effect that it causes in the SMOS brightness temperatures.

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.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission was launched 2 Nov 2009 and, to date, is still in good health, providing valuable L-band observations of the Earth surface [1]. A number of products are obtained from these, including thin sea ice [2], frost/thaw soils [3], high winds [4], ocean surface wind [5] and Sun brightness temperature [6], besides the main mission measurements of soil moisture and sea surface salinity [7] [8]. This paper deals with the description and early results of some technology activities conducted by ESA applying the lessons learnt by SMOS and in preparation of an advanced L-band radiometer mission.

In this work, a methodology to correct the Faraday Rotation Angle (FRA) is presented. It consists of calculating a systematic error pattern introduced by MIRAS, which is calculated in zones where the FRA tends to zero. Once calculated, this error is subtracted in the rest of the measurements. In both cases, the FRA is calculated following a process of minimization of the equation that relates the SMOS full polarization radiometric measurements to that parameter.

16th Specialist Meeting on on Microwave Radiometry and Remote Sensing of the Environment, 16-20 November 2020

In microwave interferometric radiometers with a large field of view, as for example the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, one of the major causes of reconstruction error is the contribution to the visibility of the brightness temperature outside the fundamental period, defined on the basis of reciprocal grids. A mitigation method consisting of estimating this contribution through the application of a brightness temperature model outside the fundamental period is proposed. The main advantage is that it does not require any a posteriori addition of artificial scenes to the reconstructed image. Additionally, a method to avoid the sophisticated matrix regularization and inversion techniques usually applied in microwave interferometry is presented. Image reconstruction algorithms are implemented on a minimum grid size in order to maximize their numerical efficiency. An improved method to apply an apodization window to the reconstructed image for reducing Gibbs oscillations is also proposed. All procedures are generally described considering the single polarization case and successively implemented applying the MIRAS layout in both its single polarization and full polarimetric modes. Results show similar performance of the proposed algorithm with respect to the nominal one applied by SMOS. All algorithms are implemented in the MIRAS Testing Software and have been successfully used for scientific studies by other teams.

In this work, a refined methodology to correct the Faraday Rotation angle (FRA) for the SMOS mission is proposed. The method is based on calculating the FRA using the SMOS full-pol radiometric data to obtain VTEC maps applying spatiotemporal filtering techniques, to then making possible the compensation of the FRA effect. By this way, the FRA would be corrected from the data that is measuring the satellite and not using an external database.

Temporal stability of the radiometer MIRAS, on board the SMOS satellite, is analyzed using long series of data spanning for about 6 years. Brightness temperature retrieved from one orbit per day over the Pacific Ocean is compared against a forward model and the difference between both is analyzed. Plots of the average in central latitudes as a function of time show small seasonal ripples (~±0.5 K) that depend on the calibration strategy chosen. An extremely low drift of only several mK/year is found and in some cases disappears. Hovmoller plots for the same data, consisting of brightness temperature biases as a function of latitude and time, confirm the small ripples and show some latitude dependent structures, probably coming from geophysical signatures.

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.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 9 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data products are generated using version v620 of the Level-1 operational processor, a version which entered into operation in Spring 2015. During last year a comprehensive data set was processed using a new processor version v720 and the assessment of the results is expected to be completed by mid 2019. In parallel to this evaluation of v720, the following version v730 of the Level-1 processor of SMOS has been already produced. This latter version is intended for investigating the capability to reduce Radio Frequency Interferences (RFI) by applying image processing techniques. This paper describes the major features and status of the two mentioned versions of the SMOS Level-1 processor, and importantly, aims at updating the remote sensing community on those aspects of the SMOS mission.

In this work, a new methodology to estimate the Faraday Rotation Angle (FRA) from SMOS full-pol brightness temperature is presented. This approach is focused on retrieving the Vertical Total Electron Content (VTEC) and then, the FRA for most of the SMOS overpass, with the final aim of improving geophysical retrievals.

Using land-sea transitions as two-level targets, the gain parameter of the three Noise Injection Radiometers (NIR) installed in instrument MIRAS onboard ESA's SMOS satellite are independently estimated. The reference data for this calibration is the average antenna temperature measured simultaneously by the other MIRAS receivers operating as total power radiometers. Individually, the retrieved parameters show similar values to the nominal sky-calibrated ones, but long-term series of data reveal different seasonal behavior, suggesting that external maneuvers may have a non-negligible impact on the NIR front-end stability.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 8 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data for this whole period has been and is being processed with the operational version of the current Level-l processor (version v620). Also a representative part of the same data set has been processed with a working version of a new processor (v720) which is now in preparation so that homogenous records of brightness temperatures have been made available. These rich and long data records have allowed learning important lessons from the in-flight experience, and shall eventually lead into the consolidation of the new Level-l processor version (v720) with its corresponding auxiliary calibration and configuration files. Once the improvements are confirmed the new processor version shall be recommended for the operational chain.

It has recently been found that the visibility denormalization process introduces a spatial error distribution due to small sporadic offset jumps in the PMS detectors. The radiometric impact of this error at system level is very low. However, due to the good performance of the SMOS instrument, a study has recently been conducted to evaluate the amplitude of such visibility errors and develop a mitigation technique. The main results of this study are summarized in this presentation.

It has recently been demonstrated that boresight averaged Faraday rotation angle (FRA) can be retrieved directly from SMOS full-pol radiometric data. However, in order to extend FRA retrievals to the full Alias-Free Field of View (AF-FoV), SMOS relatively poor pixel radiometric sensitivity and accuracy must be compensated by spatial and temporal averaging. This requires some kind of tradeoff to constrain systematic FRA estimation bias both within SMOS AF-FoV and along the orbit. This work presents the first results given by a SMOS end-to-end FRA simulator, currently under development, that is used to trim and assess the performance of several FRA retrieval approaches.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for over 7 years, with its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) functioning well. This 7 year period has provided a wealth of information which has enabled us to understand and consolidate the performance of the payload in great detail. More importantly, we know now the things that work well, those that need improvement, and how the instrument could be enhanced if we were to build it again. This paper presents the lessons learnt from SMOS after 7 years in orbit.