The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. The commissioning phase ended in May 2010. Subsequently, the satellite ...has been in operation for over six years while the retrieval algorithms from Level 1 (L1) to Level 2 (L2) underwent significant evolutions as knowledge improved. Moreover, other approaches for retrieval at L2 over land were investigated while Level 3 (L3) and Level 4 (L4) were initiated. In this paper, these improvements were assessed by inter-comparisons of the current L2 (V620) against the previous version (V551) and new products (using neural networks referred to as SMOS-NN) and L3 (referred to as SMOS-L3). In addition, a global evaluation of different SMOS soil moisture (SM) products (SMOS-L2, SMOS-L3, and SMOS-NN) was performed comparing products with those of model simulations and other satellites. Finally, all products were evaluated against in situ measurements of soil moisture (SM). To achieve such a goal a set of metrics to evaluate different satellite products are suggested.
The study demonstrated that the V620 shows a significant improvement (including those at L1 improving L2) with respect to the earlier version V551. Results also show that neural network based approaches can often yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved through the significant reduction of RFI sources in several areas of the world. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.
•First extensive evaluation of SMOS soil moisture products•Using all possible elements of comparison•Against sites, networks, model outputs and other satellite data•Spatial and temporal aspects also covered•Based on latest version of products
The SMOS Soil Moisture Retrieval Algorithm Kerr, Y. H.; Waldteufel, P.; Richaume, P. ...
IEEE transactions on geoscience and remote sensing,
05/2012, Letnik:
50, Številka:
5
Journal Article
Recenzirano
Odprti dostop
The Soil Moisture and Ocean Salinity (SMOS) mission is European Space Agency (ESA's) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint program between ESA Centre ...National d'Etudes Spatiales (CNES) and Centro para el Desarrollo Tecnologico Industrial. SMOS carries a single payload, an L-Band 2-D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere, and hence the instrument probes the earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. The goal of the level 2 algorithm is thus to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3. To reach this goal, a retrieval algorithm was developed and implemented in the ground segment which processes level 1 to level 2 data. Level 1 consists mainly of angular brightness temperatures (TB), while level 2 consists of geophysical products in swath mode, i.e., as acquired by the sensor during a half orbit from pole to pole. In this context, a group of institutes prepared the SMOS algorithm theoretical basis documents to be used to produce the operational algorithm. The principle of the SM retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modeled TB data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g., SM and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains SM, vegetation opacity, and estimated dielectric constant of any surface, TB computed at 42.5°, flags and quality indices, and other parameters of interest. This paper gives an overview of the algorithm, discusses the caveats, and provides a glimpse of the Cal Val exercises.
A technique to retrieve surface soil moisture was assessed at the global scale using a synthetic data set of L‐band (1.4 GHz) brightness temperatures TB for 2 years, 1987 and 1988. The global TB ...database consists of half‐degree continental pixels and accounts for within‐pixel heterogeneity, on the basis of 1 km resolution land cover maps. The retrievals were performed using a three‐parameter inversion method applied to the L‐band Microwave Emission of Biosphere model (L‐MEB). Three land surface variables were retrieved simultaneously from the multiangular and dual‐polarization TB data: surface soil moisture wg, vegetation optical depth τ, and surface temperature TS. The retrievals were obtained in two TS configurations: TS was either unknown or known with an uncertainty of 2 K. Applying these two assumptions, global maps of the estimated accuracy of the wg retrievals were produced, and the capability of the TB to monitor wg was evaluated. A sensitivity study was carried out in order to analyze the effect of the main parameters that may affect the retrieval accuracy: the fraction cover of open water and forests, frozen soil conditions, and the radiometric noise on TB. These results contribute to the better definition of the potential of the observations from future spaceborne missions such as the Soil Moisture and Ocean Salinity (SMOS) project.
It is now well understood that data on soil moisture and sea surface salinity (SSS) are required to improve meteorological and climate predictions. These two quantities are not yet available globally ...or with adequate temporal or spatial sampling. It is recognized that a spaceborne L-band radiometer with a suitable antenna is the most promising way of fulfilling this gap. With these scientific objectives and technical solution at the heart of a proposed mission concept the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) mission as its second Earth Explorer Opportunity Mission. The development of the SMOS mission was led by ESA in collaboration with the Centre National d'Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Tecnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L-Band 2-D interferometric radiometer operating in the 1400–1427-MHz protected band 1. The instrument receives the radiation emitted from Earth's surface, which can then be related to the moisture content in the first few centimeters of soil over land, and to salinity in the surface waters of the oceans. SMOS will achieve an unprecedented maximum spatial resolution of 50 km at L-band over land (43 km on average over the field of view), providing multiangular dual polarized (or fully polarized) brightness temperatures over the globe. SMOS has a revisit time of less than 3 days so as to retrieve soil moisture and ocean salinity data, meeting the mission's science objectives. The caveat in relation to its sampling requirements is that SMOS will have a somewhat reduced sensitivity when compared to conventional radiometers. The SMOS satellite was launched successfully on November 2, 2009.
Le ministre Hubert Curien Waldteufel, Philippe
Histoire de la recherche contemporaine,
2016
Journal Article
Odprti dostop
Pendant ses mandats ministériels (1984-1986 puis 1988-1993), Hubert Curien a donné une forte visibilité à la recherche au sein de l’action gouvernementale. Il a agi dans tous les domaines : outils de ...pilotage (tableaux de bord, prospective, évaluation) ; renforcement de l’organisation de la recherche publique ; cohérence accrue du Budget civil de recherche ; montée en puissance de la recherche industrielle ; développement des rapports entre science, société et citoyen… sans oublier la prédilection pour l’Espace ni, surtout, la priorité qu’Hubert Curien a, toute sa vie durant, donnée à la formation par la recherche.
The Soil Moisture and Ocean Salinity (SMOS) mission is aimed at monitoring, globally, surface soil moisture and sea surface salinity from radiometric L‐band observations. The SMOS radiometer relies ...upon a two‐dimensional (2‐D) synthetic aperture concept in order to achieve satisfactory spatial resolution performances for a minimal cost in terms of payload mass and volume. Counterparts of this advantage are reduced radiometric sensitivity and increased complexity. The performances expected from SMOS, in terms of measurement accuracy, spatial resolution, and revisit time, depend on many parameters, among which several are crucial for assessing the payload and mission configurations. Most prominent among those configuration parameters are the flight altitude, the length of the interferometer arms, the spacing between radiating elements, and the tilt angle of the antenna plane. Their selection has to be optimized, so as to satisfy both scientific requirements and main technical constraints. This paper describes the way the optimization was carried out during the SMOS phase A. After assessing the main drivers on instrument configuration from the science requirements, the goal was to find an optimal trade‐off, minimizing technical challenges while fulfilling the science objectives. It was found that, even though salinity retrievals are the most challenging, soil moisture retrievals were the most demanding in terms of mission definition and that a configuration exists to satisfy the required retrieval accuracies. The obtained configuration was then checked against ocean salinity retrievals and found satisfactory.
In the near future, the SMOS (Soil Moisture and Ocean Salinity) mission will provide global maps of surface soil moisture (SM). The SMOS baseline payload is an L-band (1.4 GHz) two dimensional ...interferometric microwave radiometer which will provide multi-angular and dual-polarization observations. In the framework of the ground segment activities for the SMOS mission an operational SMOS Level 2 Soil Moisture algorithm was developed. The principle of the algorithm is to exploit multi-angular data in order to retrieve simultaneously several surface parameters including soil moisture and vegetation characteristics. The algorithm uses an iterative approach, minimizing a cost function computed from the differences between measured and modelled brightness temperature (
T
B) data, for all available incidence angles.
In the algorithm, the selected forward model is the so-called L-MEB (L-band Microwave Emission of the Biosphere) model which was the result of an extensive review of the current knowledge of the microwave emission of various land covers. This model is a key element in the SMOS L2 algorithm and could be used in future assimilation studies. There is thus a strong need for a reference study, describing the model and its implementation. In order to address these needs a detailed description of soil and vegetation modelling in L-MEB is given in this study. In a second step, the use of L-MEB in soil moisture retrievals is evaluated for several experimental data sets over agricultural crops. Calibrations of the soil and vegetation L-MEB parameters are investigated for corn, soybean and wheat. Over the different experiments, very consistent results are obtained for each vegetation type in terms of calibration and soil moisture retrievals.
Earlier studies have pointed out systematic differences between sea surface salinity retrieved from L-band radiometric measurements and measured in situ , which depend on sea surface temperature ...(SST). We investigate how to cope with these differences given existing physically based radiative transfer models. In order to study differences coming from seawater dielectric constant parametrization, we consider the model of Somaraju and Trumpf (2006) (ST) which is built on sound physical bases and close to a single relaxation term Debye equation. While ST model uses fewer empirically adjusted parameters than other dielectric constant models currently used in salinity retrievals, ST dielectric constants are found close to those obtained using the Meissner and Wentz (2012) (MW) model. The ST parametrization is then slightly modified in order to achieve a better fit with seawater dielectric constant inferred from SMOS data. Upgraded dielectric constant model is intermediate between KS and MW models. Systematic differences between SMOS and in situ salinity are reduced to less than +/−0.2 above 0 °C and within +/−0.05 between 7 °C and 28 °C. Aquarius salinity becomes closer to in situ salinity, and within +/−0.1. The order of magnitude of remaining differences is very similar to the one achieved with the Aquarius version 5 empirical adjustment of wind model SST dependence. The upgraded parametrization is recommended for use in processing the SMOS data. Further assessment or improvement using new laboratory measurements should consider keeping the physics-based formulation by ST that has been shown here to be very efficient.
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