SMOS: The Mission and the System

Soil Moisture and Ocean Salinity (SMOS) is an Earth observation mission developed by the European Space Agency in cooperation with the Centre National d'Etudes Spatiales, France and the Centre for the Development of Industrial Technology, Spain, whose main objective is to provide global maps of soil moisture over land and sea surface salinity over oceans. This paper describes the SMOS mission in terms of the mission objectives and associated key system requirements, the conceptual implementation of the mission and corresponding system architecture, major building blocks and associated functions, the SMOS selected polar orbit and characteristics, and SMOS satellite attitude modes for the different phases of the mission and for the calibration of the Microwave Imaging Radiometer with Aperture Synthesis instrument.     

Earth-Viewing L-Band Radiometer Sensing of Sea Surface Scattered Celestial Sky Radiation—Part II: Application to SMOS

We examine how the rough sea surface scattering of L-band celestial sky radiation might affect the measurements of the future European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. For this purpose, we combined data from several surveys to build a comprehensive all-sky L-band celestial sky brightness temperature map for the SMOS mission that includes the continuum radiation and the hydrogen line emission rescaled for the SMOS bandwidth. We also constructed a separate map of strong and very localized sources that may exhibit L-band brightness temperatures exceeding 1000 K. Scattering by the roughened ocean surface of radiation from even the strongest localized sources is found to reduce the contributions from these localized strong sources to negligible levels, and rough surface scattering solutions may be obtained with a map much coarser than the original continuum maps. In rough ocean surface conditions, the contribution of the scattered celestial noise to the reconstructed brightness temperatures is not significantly modified by the synthetic antenna weighting function, which makes integration over the synthetic beam unnecessary. The contamination of the reconstructed brightness temperatures by celestial noise exhibits a strong annual cycle with the largest contamination occurring in the descending swaths in September and October, when the specular projection of the field of view is aligned with the Galactic equator. Ocean surface roughness may alter the contamination by over 0.1 K in 30% of the SMOS measurements. Given this potentially large impact of surface roughness, an operational method is proposed to account for it in the SMOS level 2 sea surface salinity algorithm.     

Soil moisture retrieval from space: the Soil Moisture and OceanSalinity (SMOS) mission

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data     

Deriving Sea Surface Salinity and Density Variations From Satellite and Aircraft Microwave Radiometer Measurements: Application to Coastal Plumes Using STARRS

Using brightness temperature Tb measurements from L-band airborne microwave radiometers, with independent sea surface temperature (SST) observations, sea surface salinity (SSS) can be remotely determined with errors of about 1 psu in temperate regions. Nonlinearities in the relationship between Tb, SSS, and SST produce variations in the sensitivity of salinity S to variations in Tb and SST. Despite significant efforts devoted to SSS remote sensing retrieval algorithms, little consideration has been given to deriving density D from remotely sensed SSS and SST. Density is related to S and T through the equation of state. It affects the ocean's static stability and its dynamical response to forcings. By chaining together two empirical relationships (flat-sea emissivity and equation of state) to form an inversion algorithm for sea surface density (SSD) in terms of Tb and SST, we develop a simple L-band SSD retrieval algorithm. We use this to investigate the sensitivity of SSD retrievals to observed Tb and SST and infer errors in D for typical sampling configurations of the airborne Salinity, Temperature, And Roughness Remote Scanner (STARRS) and satellite-borne Soil Moisture and Ocean Salinity (SMOS) and Aquarius radiometers. We then derive D from observations of river plumes obtained using STARRS and demonstrate several oceanographic applications: the observations are used to study variations in T and S effects on D in the Mississippi plume, and the across-shelf density gradient is used to infer surface geostrophic shear and subsurface geostrophic current in the Plata plume. Future basin-scale applications of SSD retrievals from satellite-borne microwave radiometers such as SMOS and Aquarius are anticipated.     

SMOS Calibration

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.     

SMOS Validation and the COSMOS Campaigns

The Soil Moisture and Ocean Salinity (SMOS) mission is a joint ESA-CNES (F)-CDTI (E) mission within the ESA Living Planet Program, and it was the second ESA Earth Explorer Opportunity Mission to be selected. The mission objectives of SMOS are to provide soil moisture and ocean salinity observations for weather forecasting, climate monitoring, and the global freshwater cycle. This paper will describe the scientific campaigns performed to date, as well as the plans for the on-orbit calibration and validation activities.     

The determination of surface salinity with the European SMOS space mission

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission aims at obtaining global maps of soil moisture and sea surface salinity from space for large-scale and climatic studies. It uses an L-band (1400-1427 MHz) Microwave Interferometric Radiometer by Aperture Synthesis to measure brightness temperature of the earth's surface at horizontal and vertical polarizations (T/sub h/ and T/sub v/). These two parameters will be used together to retrieve the geophysical parameters. The retrieval of salinity is a complex process that requires the knowledge of other environmental information and an accurate processing of the radiometer measurements. Here, we present recent results obtained from several studies and field experiments that were part of the SMOS mission, and highlight the issues still to be solved.     

Sea Surface Salinity Retrieval for the SMOS Mission Using Neural Networks

During the in-flight phase, using neural networks to retrieve the sea surface salinity from the observed Soil Moisture and Ocean Salinity brightness temperatures (TBs) is an empirical approach that offers the possibility of being independent from any theoretical emissivity model. Due to the large variety of incidence angles, several networks are needed, as well as a preprocessing phase to adapt the observed TBs to the inputs of the networks. When using the first Stokes parameter as an input, the retrieved salinity has a good accuracy (with an error of around 0.6 psu). Furthermore, the solutions for improving these performances are discussed.     

MIRAS end-to-end calibration: application to SMOS L1 processor

End-to-end calibration of the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) radiometer refers to processing the measured raw data up to dual-polarization brightness temperature maps over the earth's surface, which is the level 1 product of the Soil Moisture and Ocean Salinity (SMOS) mission. The process starts with a self-correction of comparators offset and quadrature error and is followed by the calibration procedure itself. This one is based on periodically injecting correlated and uncorrelated noise to all receivers in order to measure their relevant parameters, which are then used to correct the raw data. This can deal with most of the errors associated with the receivers but does not correct for antenna errors, which must be included in the image reconstruction algorithm. Relative S-parameters of the noise injection network and of the input switch are needed as additional data, whereas the whole process is independent of the exact value of the noise source power and of the distribution network physical temperature. On the other hand, the approach relies on having at least one very well-calibrated reference receiver, which is implemented as a noise injection radiometer. The result is the calibrated visibility function, which is inverted by the image reconstruction algorithm to get the brightness temperature as a function of the director cosines at the antenna reference plane. The final step is a coordinate rotation to obtain the horizontal and vertical brightness temperature maps over the earth. The procedures presented are validated using a complete SMOS simulator previously developed by the authors.     

The NAFE'05/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation

The National Airborne Field Experiment 2005 (NAFE'05) and the Campaign for validating the Operation of Soil Moisture and Ocean Salinity (CoSMOS) were undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. The objective of the joint campaign was to provide simulated Soil Moisture and Ocean Salinity (SMOS) observations using airborne L-band radiometers supported by soil moisture and other relevant ground data for the following: (1) the development of SMOS soil moisture retrieval algorithms; (2) developing approaches for downscaling the low-resolution data from SMOS; and (3) testing its assimilation into land surface models for root zone soil moisture retrieval. This paper describes the NAFE'05 and CoSMOS airborne data sets together with the ground data collected in support of both aircraft campaigns. The airborne L-band acquisitions included 40 km times 40 km coverage flights at 500-m and 1-km resolution for the simulation of a SMOS pixel, multiresolution flights with ground resolution ranging from 1 km to 62.5 m, multiangle observations, and specific flights that targeted the vegetation dew and sun glint effect on L-band soil moisture retrieval. The L-band data were accompanied by airborne thermal infrared and optical measurements. The ground data consisted of continuous soil moisture profile measurements at 18 monitoring sites throughout the 40 km times 40 km study area and extensive spatial near-surface soil moisture measurements concurrent with airborne monitoring. Additionally, data were collected on rock coverage and temperature, surface roughness, skin and soil temperatures, dew amount, and vegetation water content and biomass. These data are available at www.nafe.unimelb.edu.au.     

A combined modeling and multispectral/multiresolution remote sensing approach for disaggregation of surface soil moisture: application to SMOS configuration

A new physically based disaggregation method is developed to improve the spatial resolution of the surface soil moisture extracted from the Soil Moisture and Ocean Salinity (SMOS) data. The approach combines the 40-km resolution SMOS multiangular brightness temperatures and 1-km resolution auxiliary data composed of visible, near-infrared, and thermal infrared remote sensing data and all the surface variables involved in the modeling of land surface-atmosphere interaction available at this scale (soil texture, atmospheric forcing, etc.). The method successively estimates a relative spatial distribution of soil moisture with fine-scale auxiliary data, and normalizes this distribution at SMOS resolution with SMOS data. The main assumption relies on the relationship between the radiometric soil temperature inverted from the thermal infrared and the microwave soil moisture. Based on synthetic data generated with a land surface model, it is shown that the radiometric soil temperature can be used as a tracer of the spatial variability of the 0-5 cm soil moisture. A sensitivity analysis shows that the algorithm remains stable for big uncertainties in auxiliary data and that the uncertainty in SMOS observation seems to be the limiting factor. Finally, a simple application to the SGP97/AVHRR data illustrates the usefulness of the approach.     

Foreword to the Special Issue on the Soil Moisture and Ocean Salinity (SMOS) Mission

The aim of this special issue to provide as much as possible an overview of the Soil Moisture and Ocean Salinity (SMOS) project now that it is reaching completion.     

Flagging the Topographic Impact on the SMOS Signal

Soil moisture retrieval models from the Soil Moisture and Ocean Salinity (SMOS) mission, which is an L-band microwave interferometer, are based on multiangular measurements and make use of the emissivity angular signature. Mountainous areas modify local incidence angles, implying significant impacts on brightness temperatures and, consequently, on soil moisture retrievals. The purpose of this paper is to establish a criterion in quantifying the relevance of topographic impacts at the SMOS scale ( ~ 40 km). The goal is thus to define a method of flagging the pixels according to the relative impact of topography on the brightness temperature. The proposed method uses the variogram of digital elevation model images. As a result, a map of the pixels to be flagged is produced to ensure that no soil moisture retrievals are carried out on pixels that are affected by strong topographic effects. As validation, a model was also used to simulate differences between brightness temperature variations between mountainous areas and flat surfaces.     

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Sea surface salinity can be measured by passive microwave remote sensing at L-band. In May 1999, the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission to provide global coverage of soil moisture and ocean salinity. To determine the effect of wind on the sea surface emissivity, ESA sponsored the Wind and Salinity Experiment (WISE 2000). This paper describes the field campaign, the measurements acquired with emphasis in the radiometric measurements at L-band, their comparison with numerical models, and the implications for the remote sensing of sea salinity.     

N-parameter retrievals from L-band microwave observations acquired over a variety of crop fields

A number of studies have shown the feasibility of estimating surface soil moisture from L-band passive microwave measurements. Such measurements should be acquired in the near future by the Soil Moisture and Ocean Salinity (SMOS) mission. The SMOS measurements will be done at many incidence angles and two polarizations. This multiconfiguration capability could be very useful in soil moisture retrieval studies for decoupling between the effects of soil moisture and of the various surface parameters that also influence the surface emission (surface temperature, vegetation attenuation, soil roughness, etc.). The possibility to implement N-parameter (N-P) retrieval methods (where N = 2, 3, 4, ..., corresponds to the number of parameters that are retrieved) was investigated in this study based on experimental datasets acquired over a variety of crop fields. A large number of configurations of the N-P retrievals were studied, using several initializations of the model input parameters that were considered to be fixed or free. The best general configuration using no ancillary information (same configuration for all datasets) provided an rms error of about 0.059 m/sup 3//m/sup 3/ in the soil moisture retrievals. If a priori information was available on soil roughness and at least one vegetation model parameter, the rms error decreased to 0.049 m/sup 3//m/sup 3/. Using specific retrieval configurations for each dataset, the rms error was generally lower than 0.04 m/sup 3//m/sup 3/.     

The effect of the ionosphere on remote sensing of sea surface salinity from space: absorption and emission at L band

The purpose of this work is to examine the effects of Faraday rotation and attenuation/emission in the ionosphere in the context of a future remote sensing system in space to measure salinity. Sea surface salinity is important for understanding ocean circulation and for modeling energy exchange with the atmosphere. A passive microwave sensor in space operating near 1.4 GHz (L-band) could provide global coverage and complement in situ arrays being planned to provide subsurface profiles. However, the salinity signal is relatively small and changes along the propagation path can be important sources of error. It is shown that errors due to the ionosphere can be as large as several psu. The dominant source of error is Faraday rotation but emission can be important     

SMOS: The Payload

The European Space Agency's Soil Moisture and Ocean Salinity satellite comprises a single payload instrument known as the Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) coupled to a PROTEUS platform. MIRAS synthesizes a large aperture from a reasonably sized 2-D array of passive microwave radiometers. By using interferometric techniques, the required coverage and spatial resolution can be achieved without the need for a large antenna. This paper describes the MIRAS instrument, its observation modes, the imaging geometry, and data products.     

Two-dimensional synthetic aperture images over a land surface scene

The Soil Moisture and Ocean Salinity (SMOS) space mission is currently undergoing phase-B studies at the European Space Agency. The SMOS payload is an L-band interferometric radiometer based on a two-dimensional aperture synthesis concept. This paper presents the first images obtained by a demonstrator of the SMOS instrument over land surfaces at the Avignon test site in 1999     

Ionospheric effects for L-band 2-D interferometric radiometry

Ionospheric effects are a potential error source for the estimation of surface quantities such as sea surface salinity, using L-band radiometry. This study is carried out in the context of the SMOS future space mission, which uses an interferometric radiometer. We first describe the way the Faraday rotation angle due to electron content along the observing path varies across the two-dimensional field of view. Over open ocean surfaces, we show that it is possible to retrieve the total electron content (TEC) at nadir from radiometric data considered over the bulk of the field of view, with an accuracy better than 0.5 TEC units, compatible with requirements for surface salinity observations. Using a full-polarimetric design improves the accuracy on the estimated TEC value. The random uncertainty on retrieved salinity is decreased by about 15% with respect to results obtained when using only data for the first Stokes parameter, which is immune to Faraday rotation. Similarly, TEC values over land surfaces may be retrieved with the accuracy required in the context of soil moisture measurements. Finally, direct TEC estimation provides information which should allow to correct for ionospheric attenuation as well.     

Retrieving soil moisture from simulated brightness temperatures bya neural network

The authors present the retrievals of surface soil moisture (SM) from simulated brightness temperatures by a newly developed error propagation learning backpropagation (EPLBP) neural network. The frequencies of interest include 6.9 and 10.7 GHz of the advanced microwave scanning radiometer (AMSR) and 1.4 GHz (L-band) of the soil moisture and ocean salinity (SMOS) sensor. The land surface process/radiobrightness (LSP/R) model is used to provide time series of both SM and brightness temperatures at 6.9 and 10.7 GHz for AMSRs viewing angle of 55°, and at L-band for SMOS's multiple viewing angles of 0°, 10°, 20°, 30°, 40°, and 50° for prairie grassland with a column density of 3.7 km/m². These multiple frequencies and viewing angles allow the authors to design a variety of observation modes to examine their sensitivity to SM. For example, L-band brightness temperature at any single look angle is regarded as an L-band one-dimensional (1D) observation mode. Meanwhile, it can be combined with either the observation at the other angles to become an L-band two-dimensional (2D) or a multiple dimensional observation mode, or with the observation at 6.9 or 10.7 GHz to become a multiple frequency/dimensional observation mode. In this paper, it is shown that the sensitivity of radiobrightness at AMSR channels to SM is increased by incorporating L-band radiobrightness. In addition, the advantage of an L-band 2D or a multiple dimensional observation mode over an L-band 1D observation mode is demonstrated