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Wolfgang Wagner - One of the best experts on this subject based on the ideXlab platform.
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Latest upgrades in the MetOp ASCAT Soil Moisture Product
2020Co-Authors: Sebastian Hahn, Thomas Melzer, Wolfgang WagnerAbstract:The MetOp ASCAT Soil Moisture Product will contribute to the most consistent and complete global ECV (essential climate variable) soil moisture data record, which will be based on different active (ERS-1/2 AMI, MetOp ASCAT) and passive (SMMR, SSM/I, TMI, AMSR-E, Windsat) microwave sensors. The MetOp ASCAT soil moisture product is computed using the current version of the Water Retrieval Package (WARP 5.4), which is based on a semi-empiric change detection method exploiting the multi-incidence angle viewing capabilities of ASCAT. However, an enhanced version (WARP 6.0) will be developed to address weaknesses in the semi-empiric model, e.g. w.r.t. arid environments. The soil moisture product generated with the new version WARP 6.0 will then serve as input in the ECV production system. The aim of the system is to merge the different soil moisture products from the various sources, in order to facilitate long-term studies like trend analysis. This study presents first results of the latest upgrades in WARP, as well as various validations using other soil moisture products (e.g. SMOS, GLDAS, in-situ).
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The Added Value of the VH/VV Polarization-Ratio for Global Soil Moisture Estimations From Scatterometer Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018Co-Authors: Felix Greifeneder, Sebastian Hahn, Christoph Reimer, Mariette Vreugdenhil, Claudia Notarnicola, Emanuele Santi, Simonetta Paloscia, Wolfgang WagnerAbstract:The successor to the current series of MetOp advanced scatterometers (ASCATs), the MetOp-SG SCA, will be able to record data in dual-polarization, at C-band. The aim of this study is to investigate if the information contained in the added cross-polarization measurements can improve the vegetation parameterization for the estimation of the soil moisture content. In case of the operational Hydrology Satellite Application Facility MetOp ASCAT soil moisture product, vegetation dynamics are characterized by the relationship between radar backscattering intensity and the incidence angle, the so-called SLOPE parameter. Building on findings from previous studies, the assumption is that the polarization ratio, i.e., VH/VV, could improve this characterization. To verify this assumption, flexible approaches, able to integrate a combination of ASCAT VV data and AQUARIUS (NASA) VH/VV data were required. Two machine learning methods were chosen: Support-vector-regression and artificial-neural-networks, and one statistical approach, the Bayesian-Regression. Each of these methods were used to derive models with different input configurations, with and without characterization of vegetation. The results show that the information contained in the SLOPE parameter and in PR are similar. Based on a global average, almost identical SMC retrieval accuracies were achieved. Despite that, analysis of the temporal dynamics of SLOPE and PR revealed certain location specific differences, which affect the spatial distribution of SMC retrieval accuracies. As a result, improvements based on the combination of the two parameters are minor overall, but they can be significant locally.
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Dynamic Characterization of the Incidence Angle Dependence of Backscatter Using MetOp ASCAT
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017Co-Authors: Sebastian Hahn, Christoph Reimer, Mariette Vreugdenhil, Thomas Melzer, Wolfgang WagnerAbstract:Observing a target from different look and incidence angles is one of the key features of the Advanced Scatterometer (ASCAT) on-board the series of MetOp satellites. The incidence angle dependency of backscatter plays an important role in extracting useful information for the retrieval of geophysical parameters. The TU Wien change detection algorithm exploits the multiangle measurement capabilities of ASCAT to retrieve relative surface soil moisture content. In the TU Wien algorithm, the incidence angle dependence of backscatter is characterized with a second-order polynomial and its coefficients are estimated from several years of data due to robustness. Recently, however, it has been shown by Melzer [1], that a kernel smoother (KS) holds promise to characterize the polynomial coefficients on an interannual basis. In this study, we tested the performance and robustness of the KS globally, by comparing the results obtained from ASCAT on-board MetOp-A and MetOp-B independently. Overall, a good agreement has been found between MetOp-A and MetOp-B confirming a robust interannual estimation of the incidence angle dependence of backscatter using the KS. However, in two cases, the prevailing conditions on the ground complicated the estimation: areas with very low signal variation and sandy deserts. An analysis of Hovmöller diagrams provided insight into seasonal variations, also revealing small remaining biases between the instruments. The dynamic characterization of the incidence angle dependence of backscatter allows to study the temporal evolution in more detail and, at the same time, moving a step further on the vegetation correction in the TU Wien soil moisture algorithm.
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Error Assessment of the Initial Near Real-Time MetOp ASCAT Surface Soil Moisture Product
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Sebastian Hahn, Thomas Melzer, Wolfgang WagnerAbstract:Since December 2008, the European Organisation for the Exploitation of Meteorological Satellites has been operationally distributing a global 25-km surface soil moisture product derived from the Advanced Scatterometer (ASCAT) onboard the meteorological operational platform (MetOp) satellite MetOp-A. Soil moisture is retrieved by using the semiempirical change detection method originally developed by the Vienna University of Technology (TU Wien) for the Active Microwave Instrument (AMI) flown on the European Remote Sensing (ERS) satellites ERS-1 and ERS-2. With the launch of the first of the three Meteorological Operational Platforms (MetOp-A) in October 2006, ASCAT onboard MetOp-A inherits and continues the role of his predecessor AMI. The original soil moisture retrieval algorithm (TU Wien model) was expected to be almost directly applicable for ASCAT with only minor changes, since the configuration and technical design is similar to the ERS scatterometers. Since the TU Wien model requires a robust historic long-term reference of scattering parameters, the initial near real-time MetOp ASCAT soil moisture product had to rely on the model parameters derived from over 15 years of ERS-1/2. However, the combination of ASCAT backscatter measurements and ERS-1/2 historic long-term reference introduced some artifacts in the soil moisture product. The objectives of this paper were to analyze and investigate the impact of the ERS-1/2 historic long-term reference on the soil moisture retrieval. An error model has been developed to quantify the effects of the two main error sources: differences in spatial resolution and absolute calibration. The results of the study show that a simple model is able to describe the artifacts in the initial near real-time MetOp ASCAT soil moisture product, which frequently occur in areas characterized by sharp backscatter contrasts. The expected overestimation of soil moisture using ERS-1/2 model parameters due to a calibration bias between AMI and ASCAT could be modeled as well.
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initial soil moisture retrievals from the MetOp a advanced scatterometer ascat
Geophysical Research Letters, 2007Co-Authors: Zoltan Bartalis, Wolfgang Wagner, Vahid Naeimi, S Hasenauer, Klaus Scipal, Hans Bonekamp, J Figa, Craig AndersonAbstract:[1] This article presents first results of deriving relative surface soil moisture from the MetOp-A Advanced Scatterometer. Retrieval is based on a change detection approach which has originally been developed for the Active MicrowaveInstrument flownonboardtheEuropeansatellites ERS-1 and ERS-2. Using model parameters derived from eight years of ERS scatterometer data, first global soil moisture maps have been produced from ASCAT data. The ASCAT data were distributed by EUMETSAT for validation purposes during the ASCAT product commissioning activities. Several recent cases of drought and excessive rainfall are clearly visible in the soil moisture data. The results confirm that seamless soil moisture time series can be expected from the series of two ERS and three MetOp scatterometers, providing global coverage on decadal time scales (from 1991 to about 2021). Thereby, operational, nearreal-time ASCAT soil moisture products will become available for weather prediction and hydrometeorological applications. Citation: Bartalis, Z., W. Wagner, V. Naeimi, S. Hasenauer, K. Scipal, H. Bonekamp, J. Figa, and C. Anderson (2007), Initial soil moisture retrievals from the MetOp-A Advanced Scatterometer (ASCAT), Geophys. Res. Lett., 34, L20401, doi:10.1029/2007GL031088.
Sebastian Hahn - One of the best experts on this subject based on the ideXlab platform.
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Latest upgrades in the MetOp ASCAT Soil Moisture Product
2020Co-Authors: Sebastian Hahn, Thomas Melzer, Wolfgang WagnerAbstract:The MetOp ASCAT Soil Moisture Product will contribute to the most consistent and complete global ECV (essential climate variable) soil moisture data record, which will be based on different active (ERS-1/2 AMI, MetOp ASCAT) and passive (SMMR, SSM/I, TMI, AMSR-E, Windsat) microwave sensors. The MetOp ASCAT soil moisture product is computed using the current version of the Water Retrieval Package (WARP 5.4), which is based on a semi-empiric change detection method exploiting the multi-incidence angle viewing capabilities of ASCAT. However, an enhanced version (WARP 6.0) will be developed to address weaknesses in the semi-empiric model, e.g. w.r.t. arid environments. The soil moisture product generated with the new version WARP 6.0 will then serve as input in the ECV production system. The aim of the system is to merge the different soil moisture products from the various sources, in order to facilitate long-term studies like trend analysis. This study presents first results of the latest upgrades in WARP, as well as various validations using other soil moisture products (e.g. SMOS, GLDAS, in-situ).
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The Added Value of the VH/VV Polarization-Ratio for Global Soil Moisture Estimations From Scatterometer Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018Co-Authors: Felix Greifeneder, Sebastian Hahn, Christoph Reimer, Mariette Vreugdenhil, Claudia Notarnicola, Emanuele Santi, Simonetta Paloscia, Wolfgang WagnerAbstract:The successor to the current series of MetOp advanced scatterometers (ASCATs), the MetOp-SG SCA, will be able to record data in dual-polarization, at C-band. The aim of this study is to investigate if the information contained in the added cross-polarization measurements can improve the vegetation parameterization for the estimation of the soil moisture content. In case of the operational Hydrology Satellite Application Facility MetOp ASCAT soil moisture product, vegetation dynamics are characterized by the relationship between radar backscattering intensity and the incidence angle, the so-called SLOPE parameter. Building on findings from previous studies, the assumption is that the polarization ratio, i.e., VH/VV, could improve this characterization. To verify this assumption, flexible approaches, able to integrate a combination of ASCAT VV data and AQUARIUS (NASA) VH/VV data were required. Two machine learning methods were chosen: Support-vector-regression and artificial-neural-networks, and one statistical approach, the Bayesian-Regression. Each of these methods were used to derive models with different input configurations, with and without characterization of vegetation. The results show that the information contained in the SLOPE parameter and in PR are similar. Based on a global average, almost identical SMC retrieval accuracies were achieved. Despite that, analysis of the temporal dynamics of SLOPE and PR revealed certain location specific differences, which affect the spatial distribution of SMC retrieval accuracies. As a result, improvements based on the combination of the two parameters are minor overall, but they can be significant locally.
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Dynamic Characterization of the Incidence Angle Dependence of Backscatter Using MetOp ASCAT
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017Co-Authors: Sebastian Hahn, Christoph Reimer, Mariette Vreugdenhil, Thomas Melzer, Wolfgang WagnerAbstract:Observing a target from different look and incidence angles is one of the key features of the Advanced Scatterometer (ASCAT) on-board the series of MetOp satellites. The incidence angle dependency of backscatter plays an important role in extracting useful information for the retrieval of geophysical parameters. The TU Wien change detection algorithm exploits the multiangle measurement capabilities of ASCAT to retrieve relative surface soil moisture content. In the TU Wien algorithm, the incidence angle dependence of backscatter is characterized with a second-order polynomial and its coefficients are estimated from several years of data due to robustness. Recently, however, it has been shown by Melzer [1], that a kernel smoother (KS) holds promise to characterize the polynomial coefficients on an interannual basis. In this study, we tested the performance and robustness of the KS globally, by comparing the results obtained from ASCAT on-board MetOp-A and MetOp-B independently. Overall, a good agreement has been found between MetOp-A and MetOp-B confirming a robust interannual estimation of the incidence angle dependence of backscatter using the KS. However, in two cases, the prevailing conditions on the ground complicated the estimation: areas with very low signal variation and sandy deserts. An analysis of Hovmöller diagrams provided insight into seasonal variations, also revealing small remaining biases between the instruments. The dynamic characterization of the incidence angle dependence of backscatter allows to study the temporal evolution in more detail and, at the same time, moving a step further on the vegetation correction in the TU Wien soil moisture algorithm.
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Error Assessment of the Initial Near Real-Time MetOp ASCAT Surface Soil Moisture Product
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Sebastian Hahn, Thomas Melzer, Wolfgang WagnerAbstract:Since December 2008, the European Organisation for the Exploitation of Meteorological Satellites has been operationally distributing a global 25-km surface soil moisture product derived from the Advanced Scatterometer (ASCAT) onboard the meteorological operational platform (MetOp) satellite MetOp-A. Soil moisture is retrieved by using the semiempirical change detection method originally developed by the Vienna University of Technology (TU Wien) for the Active Microwave Instrument (AMI) flown on the European Remote Sensing (ERS) satellites ERS-1 and ERS-2. With the launch of the first of the three Meteorological Operational Platforms (MetOp-A) in October 2006, ASCAT onboard MetOp-A inherits and continues the role of his predecessor AMI. The original soil moisture retrieval algorithm (TU Wien model) was expected to be almost directly applicable for ASCAT with only minor changes, since the configuration and technical design is similar to the ERS scatterometers. Since the TU Wien model requires a robust historic long-term reference of scattering parameters, the initial near real-time MetOp ASCAT soil moisture product had to rely on the model parameters derived from over 15 years of ERS-1/2. However, the combination of ASCAT backscatter measurements and ERS-1/2 historic long-term reference introduced some artifacts in the soil moisture product. The objectives of this paper were to analyze and investigate the impact of the ERS-1/2 historic long-term reference on the soil moisture retrieval. An error model has been developed to quantify the effects of the two main error sources: differences in spatial resolution and absolute calibration. The results of the study show that a simple model is able to describe the artifacts in the initial near real-time MetOp ASCAT soil moisture product, which frequently occur in areas characterized by sharp backscatter contrasts. The expected overestimation of soil moisture using ERS-1/2 model parameters due to a calibration bias between AMI and ASCAT could be modeled as well.
Pierre-françois Coheur - One of the best experts on this subject based on the ideXlab platform.
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French/Belgian scientific contribution to tropospheric studies using the MetOp sensors
2020Co-Authors: Cathy Clerbaux, Solène Turquety, D. Hauglustaine, Matthias Beekmann, Claude Camy-peyret, Sébastien Payan, Johannes Orphal, Pierre-françois Coheur, Jean-françois Müller, Martine De MazièreAbstract:We propose to combine the tropospheric measurements provided by the IASI and GOME2 instruments aboard MetOp, together with data from ground-based stations, airborne and spaceborne remote sensors, along with atmospheric chemistry models (CTMs) in order to improve our knowledge of processes constraining the chemical composition of the troposphere and to study the regional and global scale air quality. The measurements of ozone (O 3), carbon monoxide (CO), nitrogen dioxide (NO2), formaldehyde (CH2O), and methane (CH4) will be used in conjunction with the 3D tropospheric LMDz-INCA, MOZART, IMAGES and CHIMERE CTM models, using data assimilation and inversion modeling techniques, to study the global distribution of these species and to derive improved emissions estimates. Before the MetOp launch, all the tools developed in the framework of this project will be used to analyse the AURA TES and OMI tropospheric products. After the launch of MetOp, the data provided by both satellites will then be analyzed with the CTMs. The resulting global distributions will be used to perform detailed studies of the role of biomass burning in the budget of tropospheric species, the emissions of ozone precursors, the role of convective transport of pollutants, and its consequences in terms of air quality.
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CO monitoring with the IASI remote sensor: global and local variability
2016Co-Authors: Maya George, Cathy Clerbaux, Pierre-françois Coheur, Juliette Hadji-lazaro, Idir Bouarar, Daniel Hurtmans, Sophie Bauduin, David P. Edwards, Merritt Deeter, Helen M. WordenAbstract:Carbon monoxide (CO) is an important trace gas for understanding air quality and atmospheric composition. It is a good tracer of pollution plumes and atmospheric dynamics. In this presentation we use both the IASI and the MOPITT data to study the global and regional CO distributions as seen from space in the thermal infrared spectral range. With two IASI instruments flying on MetOp-A and MetOp-B, any location on Earth is now observed at least four times per day. All cloud free observations are analysed in near real time mode. IASI and MOPITT data are jointly assimilated in the Copernicus Atmospheric Monitoring Service to generate CO pollution forecasts. We will discuss differences at the hemispheric and regional scales, and study trends over the overlapping period. Local pollution events will also be presented, and the sensitivity of the IASI observations at surface level will be discussed. Advices on how to access and how to optimize the use of this huge dataset will be provided.
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Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables
Atmospheric Measurement Techniques, 2014Co-Authors: Cyril Crevoisier, Cathy Clerbaux, Claude Camy-peyret, Pierre-françois Coheur, Vincent Guidard, Thierry Phulpin, Raymond Armante, Blandine Barret, Jean-pierre Chaboureau, Laurent CrépeauAbstract:Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the MetOp satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the MetOp-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/MetOp series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative.
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validation of the MetOp a total ozone data from gome 2 and iasi using reference ground based measurements at the iberian peninsula
Remote Sensing of Environment, 2011Co-Authors: M Anton, Diego Loyola, M Lopez, J M Vilaplana, M Banon, Walter Zimmer, Pieter Valks, Cathy Clerbaux, Juliette Hadjilazaro, Pierre-françois CoheurAbstract:One of the most important atmospheric composition products derived from the first EUMETSAT Meteorological Operational satellite (MetOp-A) is the total ozone column (TOC). For this purpose, MetOp-A has two instruments on board: the Global Ozone Monitoring Experiment 2 (GOME-2) that retrieves the TOC data from the backscattered solar ultraviolet–visible (UV–Vis) radiance, and the Infrared Atmospheric Sounding Interferometer (IASI) that uses the thermal infrared radiance to derive TOC data. This paper focuses on the simultaneous validation of the TOC data provided by these two MetOp-A instruments using the measurements recorded by five well-calibrated Brewer UV spectrophotometers located at the Iberian Peninsula during the complete 2009. The results show an excellent correlation between the ground-based data and the GOME-2 and IASI satellite observations (R2 higher than 0.91). Differences between the ground-based and satellite TOC data show that the IASI instrument significantly overestimates the Brewer measurements (about 4.4% when all five ground-based stations are jointly used). In contrast, the GOME-2 instrument shows a slight underestimation (~ 1.6%). In addition, the absolute relative differences between the Brewer and GOME-2 data are quite smaller (about a factor higher than 2) than the Brewer–IASI absolute differences. The satellite viewing geometry (solar zenith angle and the view zenith angle) has no significant influence on the Brewer–satellite relative differences. Moreover, the analysis of these relative differences with respect to the ground-based TOC data indicates that GOME-2 instrument presents a slight underestimation for high TOC values. Finally, the IASI–GOME-2 correlation is high (R2 ~ 0.92), but with a mean relative difference of about ± 6% which could be associated with the bias between UV–Vis and infrared spectroscopy used in the retrieval processes.
M. A. Brown - One of the best experts on this subject based on the ideXlab platform.
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Radiometric Calibration of the Advanced Wind Scatterometer Radar ASCAT Carried Onboard the MetOp-A Satellite
IEEE Transactions on Geoscience and Remote Sensing, 2010Co-Authors: J J W Wilson, C. Anderson, Figa J. Saldana, H. Bonekamp, M A Baker, R. G. Dyer, J. A. Lerch, G. Kayal, R. V. Gelsthorpe, M. A. BrownAbstract:The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument is carried by each of the three MetOp satellites. The ASCAT calibration strategy is described and detailed results are presented concerning the radiometric calibration achieved.
Craig Anderson - One of the best experts on this subject based on the ideXlab platform.
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ASCAT-C Commissioning: First Cross-Comparison and Validation Results
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019Co-Authors: Francesca Ticconi, Craig Anderson, Stefanie Linow, Julian WilsonAbstract:Following the recent launch of the ESA/EUMETSAT MetOp-C satellite on 7th November 2018, this paper will provide the first results of the cross-calibration and validation activities performed during the commissioning phase of the Advanced Scatterometer (ASCAT) instrument. The ASCAT-C Level 1 data have been compared with the data of the previous ASCAT instruments on board the MetOp-A and MetOp-B satellites, which have been launched in 2006 and 2012, respectively, and are both still fully operational. The comparison has been performed over the Amazon rainforest with the aim to also validate the measured backscattering values by using such natural and homogeneous target.
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Day-2 product developments for MetOp-A
Proceedings of SPIE, 2009Co-Authors: K. Dieter Klaes, Craig Anderson, Peter Schlüssel, Jörg Ackermann, Hans Bonekamp, Rosemary Munro, Axel Von Engeln, Thomas August, Olusoji Oduleye, Johannes SchmetzAbstract:Since October 2006 EUMETSAT is flying the first operational European meteorological polar orbiting satellite MetOp-A as the morning orbit part of the Initial Joint Polar System (IJPS) with the U.S. MetOp-A is the first of a series of three in the frame of the EUMETSAT Polar System and carries a payload of eight meteorological instruments which provide inter alia sounding information for numerical weather prediction, ocean surface information, information on ozone and atmospheric chemistry. Most of the planned products are now operational. In addition, so called Day-2 products are developed or have already been developed. Such products include Soil Moisture from the Advanced Scatterometer ASCAT, a Vegetation index from the AVHRR imager and polar cap winds from AVHRR. About two years after the launch the first of these products have become operational: The soil moisture. The paper will discuss the first delivered Day-2 products and outline future development aspects. Future Day-2 products address improved radio occultation with the GRAS instrument and synergistic use of instruments for trace gas observations.
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initial soil moisture retrievals from the MetOp a advanced scatterometer ascat
Geophysical Research Letters, 2007Co-Authors: Zoltan Bartalis, Wolfgang Wagner, Vahid Naeimi, S Hasenauer, Klaus Scipal, Hans Bonekamp, J Figa, Craig AndersonAbstract:[1] This article presents first results of deriving relative surface soil moisture from the MetOp-A Advanced Scatterometer. Retrieval is based on a change detection approach which has originally been developed for the Active MicrowaveInstrument flownonboardtheEuropeansatellites ERS-1 and ERS-2. Using model parameters derived from eight years of ERS scatterometer data, first global soil moisture maps have been produced from ASCAT data. The ASCAT data were distributed by EUMETSAT for validation purposes during the ASCAT product commissioning activities. Several recent cases of drought and excessive rainfall are clearly visible in the soil moisture data. The results confirm that seamless soil moisture time series can be expected from the series of two ERS and three MetOp scatterometers, providing global coverage on decadal time scales (from 1991 to about 2021). Thereby, operational, nearreal-time ASCAT soil moisture products will become available for weather prediction and hydrometeorological applications. Citation: Bartalis, Z., W. Wagner, V. Naeimi, S. Hasenauer, K. Scipal, H. Bonekamp, J. Figa, and C. Anderson (2007), Initial soil moisture retrievals from the MetOp-A Advanced Scatterometer (ASCAT), Geophys. Res. Lett., 34, L20401, doi:10.1029/2007GL031088.