M. Drusch

European Center For Medium Range Weather Forecasts, Shinfield, England, United Kingdom

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Publications (72)73.29 Total impact

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    ABSTRACT: Microwave radiometry L-band SMOS SMAP Radiative transfer Snow Soil freeze/thaw Passive L-band (1–2 GHz) observables are sensitive to surface soil moisture and ocean salinity, which is the core of the "soil moisture and ocean salinity" (SMOS) mission of the European Space Agency (ESA). This work investigates microwave emission processes that are important to link L-band brightness temperatures with soil freeze/ thaw states and the presence and the state of snow. To this end, a ground snow radiative transfer (GS RT) model has been developed on the basis of the "Microwave Emission Model of Layered Snowpacks" (MEMLS). Our model sensitivity study revealed that L-band emission of a freezing ground can be affected significantly by dry snow, which has been mostly disregarded in previous studies. Simulations suggest that even dry snow with mostly negligible absorption at the L-band can impact L-band emission of winter landscapes significantly. We found that impedance matching and refraction caused by a dry snowpack can increase or decrease L-band emission depending on the polarization and the observation angle. Based on the performed sensitivity study, these RT processes can be compensatory at vertical polarization and the observation angle of 50°. This suggests the use of vertical polarized brightness temperatures measured at around 50° in order to achieve segregated information on soil-frost. Furthermore, our simulations demonstrate a significant sensitivity of L-band emission at horizontal polarization with respect to the density of the lowest snow layer as the result of refraction and impedance matching by the snowpack.
    Remote Sensing of Environment 08/2014; 154:180-191. · 5.10 Impact Factor
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    ABSTRACT: We present a novel algorithm for detecting seasonal soil freezing processes using L-band microwave radiometry. L-band is the optimal choice of frequency for the monitoring of soil freezing, due to the inherent high contrast of the microwave signature between the frozen and thawed states of the soil medium. Dual-polarized observations of L-band brightness temperature at a range of observation angles were collected from a tower-based instrument, and evaluated against ancillary information on soil and snow properties over four winter seasons. During the first three winter periods the measurement site was located over mineral soil on a forest clearing, for the fourth winter the instrument was moved to a wetland site. Both sites are located in Sodankylä, Northern Finland. The test sites represent two environments typical for the northern boreal forest zone. The data were applied to derive an empirical relation between the onset and progress of soil freezing and the observed passive L-band signature. A retrieval algorithm was developed using the observations at the forest opening site. The algorithm exploits the perceived change in brightness temperature and the change in the relative difference between the signatures at horizontal and vertical polarization. With the collected experimental dataset, these features were linked optimally to the progress of soil freezing by choice of observation angle, polarization and temporal averaging. The wetland site observations provided the first opportunity for demonstrating the developed algorithm over a different soil type, giving a first estimate of the algorithm performance over larger heterogeneous targets. The future objective is to adapt the algorithm to L-band satellite observations. The present study is highly relevant for the development of freeze–thaw algorithms from current and future L-band satellite missions such as SMOS and SMAP.
    Remote Sensing of Environment 05/2014; 147:206–218. · 5.10 Impact Factor
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    ABSTRACT: In a recent paper, Leroux et al. [1] compared three satellite soil moisture data sets (SMOS, AMSR-E, and ASCAT) and ECMWF forecast soil moisture data to in situ measurements over four watersheds located in the United States. Their conclusions stated that SMOS soil moisture retrievals represent “an improvement [in RMSE] by a factor of 2- 3 compared with the other products” and that the ASCAT soil moisture data are “very noisy and unstable”. In this clarification, the analysis of Leroux et al. is repeated using a newer version of the ASCAT data and additional metrics are provided. It is shown that the ASCAT retrievals are skillful, although they show some unexpected behavior during summer for two of the watersheds. It is also noted that the improvement of SMOS by a factor of 2-3 mentioned by Leroux et al. is driven by differences in bias and only applies relative to AMSR-E and the ECWMF data in the now obsolete version investigated by Leroux et al.
    IEEE Transactions on Geoscience and Remote Sensing 05/2014; 52(3):1901-1906. · 3.47 Impact Factor
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    ABSTRACT: The launch of the SMOS mission 2-Nov-2009 marked a milestone in remote sensing for it was the first time a radiometer capable of acquiring wide field of view images at every single snapshot, a unique feature of the synthetic aperture technique, made it to space. The technology behind such an achievement was developed thanks to the effort of a community of researchers and engineers in different groups around the world. It was only because of their joint work that SMOS finally became a reality. The fact that the European Space Agency, together with CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnológico e Industrial), managed to get the project through should be considered a merit and a reward for that entire community. This paper is an invited historical review that, within a very limited number of pages, tries to provide insight into some of the developments which, one way or another, are imprinted in the name of SMOS.
    Radio Science. 04/2014;
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    ABSTRACT: Following the launch of ESA's Soil Moisture and Ocean salinity (SMOS) mission it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In a first demonstration study, sea ice thickness has been derived using a semi-empirical algorithm with constant tie-points. Here we introduce a novel iterative retrieval algorithm that is based on a sea ice thermodynamic model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within a SMOS footprint are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS based sea ice thickness data set from 2010 on. This data set is compared and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study.
    The Cryosphere Discussions 12/2013; 7(6):5735-5792.
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    ABSTRACT: The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.
    The Cryosphere Discussions 11/2013; 7(6).
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    ABSTRACT: The Fluorescence Explorer (FLEX) mission is currently subject to feasibility (Phase A) study as one of the two candidates of ESA's 8th Earth Explorer opportunity mission. The FLuORescence Imaging Spectrometer (FLORIS) will be an imaging grating spectrometer onboard of a medium sized satellite flying in tandem with Sentinel-3 in a Sun synchronous orbit at a height of about 815 km. FLORIS will observe vegetation fluorescence and reflectance within a spectral range between 500 nm and 780 nm. It will thereby cover the photochemical reflection features between 500 nm and 600 nm, the Chlorophyll absorption band between 600 and 677 nm, and the red-edge in the region from 697 nm to 755 nm being located between the Oxygen A and B absorption bands. By this measurement approach, it is expected that the full spectrum and amount of the vegetation fluorescence radiance can be retrieved, and that atmospheric corrections can efficiently be applied. FLORIS will measure Earth reflected spectral radiance at a relatively high spectral resolution of ~0.3 nm around the Oxygen absorption bands. Other spectral band areas with less pronounced absorption features will be measured at medium spectral resolution between 0.5 and 2 nm. FLORIS will provide imagery at 300 m resolution on ground with a swath width of 150 km. This will allow achieving global revisit times of less than one month so as to monitor seasonal variations of the vegetation cycles. The mission life time is expected to be at least 4 years. The fluorescence retrieval will make use of information coming from OLCI and SLSTR, which are onboard of Sentinel-3, to monitor temperature, to detect thin clouds and to derive vegetation reflectance and information on the aerosol content also outside the FLORIS spectral range. In order to mitigate the technological and programmatic risk of this Explorer mission candidate, ESA has initiated two comprehensive bread-boarding activities, in which the most critical technologies and instrument performance shall be investigated and demonstrated. The breadboards will include representative optics and dispersive elements in a configuration, which is expected to be very close to the instrument flight configuration. This approach follows the guideline to reach, before it goes into the implementation phase, a technology readiness level of at least 5. It thereby requires a demonstration of predicted performance in a configuration, where the basic technological components are integrated with reasonably realistic supporting elements such that it can be tested in a simulated environment. We will report, within the limits of the competitive nature of the industrial studies, on the currently running or planned preparatory activities. We will present the mission configuration, the imposed instrument requirements and the identified instrument concepts as derived by the Phase A studies.
    Proc SPIE 10/2013;
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    ABSTRACT: Vegetation fluorescence when measured from space contributes only a tiny fraction of the signal coming on top of the reflected radiance by the Earth surface and the atmosphere. As a consequence, imaging spectrometers have to provide sufficient throughput and radiometric accuracy to enable accurate global monitoring of the daily to seasonal variations of the Earth's vegetation breath, which is particularly challenging if ground resolutions of a few hundred meters are targeted. Since fluorescence retrieval algorithms have to make corrections for atmospheric effects, it is necessary to provide sufficient spectral resolution, so that signal alterations due to the main parameters such as surface pressure, atmospheric temperature profile, vertical distribution of aerosols concentration, and water vapour content can be accurately modelled. ESA's Earth Explorer 8 candidate mission FLEX carries a Fluorescence Imaging Spectrometer (FLORIS), which has been designed and optimised to enable such measurement. The spectrometer will measure in a spectral range between 500 and 780 nm and provide high spectral resolution of 0.3 nm in particular at the Oxygen-A and -B bands. It will also cover the photochemical reflection features between 500 and 600 nm, the Chlorophyll absorption region between 600 and 677 nm, and the red-edge in the region of 697 to 755 nm. FLEX will fly in formation with Sentinel-3 in order to further enhance the spectral coverage from measurements made by the Sentinel-3 instruments OLCI and SLSTR, particularly for cloud screening and proper characterization of the atmospheric status.
    Proc SPIE 09/2013;
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    ABSTRACT: Sea ice thickness information is needed for climate modeling and ship operations. Here a method to detect the thickness of sea ice up to 50 cm during the freezeup season based on high incidence angle observations of the Soil Moisture and Ocean Salinity (SMOS) satellite working at 1.4 GHz is suggested. By comparison of thermodynamic ice growth data with SMOS brightness temperatures, a high correlation to intensity and an anti correlation to the difference between vertically and horizontally polarised brightness temperatures at incidence angles between 40 and 50 ° are found and used to develop an empirical retrieval sensitive to thin sea ice up to 50 cm thickness. It shows high correlations with ice thickness data from airborne measurements and reasonable ice thickness patterns for the Arctic freeze up period.
    The Cryosphere Discussions 08/2013; 7(4):4379-4405.
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    ABSTRACT: Correct parameterization of radiative transfer models is very important for high accuracy soil moisture retrievals from spaceborne L-band passive microwave sensors, such as the ESA Soil Moisture and Ocean Salinity (SMOS) Mission. In order to investigate the characteristics of radiative transfer parameters such as vegetation opacity and soil surface roughness, a dual state and parameter update data assimilation system has been developed. By assimilating SMOS brightness temperatures into the L-band Microwave Emission of the Biosphere (L-MEB) model, respective parameters can be estimated. The data assimilation system makes use of a temporal smoothing algorithm based on the Sampling Importance Resampling Particle Filter. The new approach, namely the Sampling Importance Resampling Particle Smoother, makes use of a particle weighting function valid not for a single time step, but for a specific time period. The resulting parameters estimated are more stable throughout the whole period under investigation, where the possibility to vary with time is still given. This is important to cover the seasonality of e.g. vegetation parameters.
    IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium; 07/2013
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    ABSTRACT: This paper presents the future European Centre for Medium-Range Weather Forecasts soil moisture analysis system based on a point-wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from both analyses are comparable. However, the EKF-based increments are generally higher for the top soil layers then for the bottom layer. This gradient better reflects the underlying hydrological processes in that the strongest interaction between soil moisture and bare soil evaporation and transpiration through vegetation should occur in top layers where most of the roots are located. The impact on the forecast skill, e.g., air temperature at 2 m and 500 hPa height, is neutral. The new EKF surface analysis system offers a range of further development options for the exploitation of satellite observations for the initialization of the land surface in Numerical Weather Prediction. Citation: Drusch, M., K. Scipal, P. de Rosnay, G. Balsamo, E. Andersson, P. Bougeault, and P. Viterbo (2009), Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System,
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    ABSTRACT: A new land surface analysis system based on a simplified point-wise Extended Kalman Filter (EKF) was implemented at the European Centre for Medium- Range Weather Forecasts in the global operational Integrated Forecasting System (IFS) in November 2010. This system will allow consistent and optimal analyses of land surface parameters like soil moisture, surface temperatures, snow and vegetation properties. As part of the system implementation, the surface analysis structure has been revised to permit an independent and parallel computation with the upper-air 4D-Var analysis. The new analysis system is used for the soil moisture analysis, replacing the previous Optimal Interpolation (OI) scheme. Similar to the OI system, the simplified EKF uses 2m air temperature and relative humidity observations from the SYNOP (land surface synoptic report) groundbased networks to analyse soil moisture. This paper describes the new land surface analysis, its application for analysing soil moisture, and initial verification results which supported its operational implementation at ECMWF. The performance is evaluated based on a set of one-year analysis experiments. The simplified EKF is compared to the OI, on soil moisture, 2m temperature and relative humidity, showing a consistent improvement on screen-level parameters and soil moisture forecasts. To demonstrate the potential of the new analysis scheme, soil moisture derived from ASCAT (Advanced Scatterometer) has been assimilated through the simplified EKF.
    Quarterly Journal of the Royal Meteorological Society 01/2013; · 3.33 Impact Factor
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    Vadose Zone Journal Special Section on Remote Sensing of Vadose Zone Hydrology. 01/2013; 12(3).
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    ABSTRACT: The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission was launched on the 2nd of November 2009. The first six months after launch, the so-called commissioning phase, were dedicated to test the functionalities of the spacecraft, the instrument, and the ground segment including the data processors. This phase was successfully completed in May 2010, and SMOS has since been in the routine operations phase and providing data products to the science community for over a year. The performance of the instrument has been within specifications. A parallel processing chain has been providing brightness temperatures in near-real time to operational centers, e.g., the European Centre for Medium-Range Weather Forecasts. Data quality has been within specifications; however, radio-frequency interference (RFI) has been detected over large parts of Europe, China, Southern Asia, and the Middle East. Detecting and flagging contaminated observations remains a challenge as well as contacting national authorities to localize and eliminate RFI sources emitting in the protected band. The generation of Level 2 soil moisture and ocean salinity data is an ongoing activity with continuously improved processors. This article will summarize the mission status after one year of operations and present selected first results.
    IEEE Transactions on Geoscience and Remote Sensing 05/2012; 50(5):1354-1366. · 3.47 Impact Factor
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    ABSTRACT: The Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) on board the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission for the first time measures globally Earth's radiation at a frequency of 1.4 GHz (L-band). It had been hypothesized that L-band radiometry can be used to measure the sea ice thickness due to the large penetration depth in the sea ice medium. We demonstrate the potential of SMOS to derive the thickness of thin sea ice for the Arctic freeze-up period using a novel retrieval algorithm based on Level 1C brightness temperatures. The SMOS ice thickness product is compared with an ice growth model and independent sea ice thickness estimates from MODIS thermal infrared imagery. The ice thickness derived from SMOS is highly consistent with the temporal development of the growth simulation and agrees with the ice thickness from MODIS images with 10 cm standard deviation. The results confirm that SMOS can be used to retrieve sea ice thickness up to half a meter under ideal cold conditions with surface air temperatures below -10°C and high-concentration sea ice coverage.
    Geophysical Research Letters 03/2012; 39(5):5501-. · 3.98 Impact Factor
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    ABSTRACT: The launch of the European Space Agency (ESA)'s Soil Moisture and Ocean Salinity (SMOS) satellite mission in November 2009 opened a new era of global passive monitoring at L-band (1.4-GHz band reserved for radio astronomy). The main objective of the mission is to measure soil moisture and sea surface salinity; the sole payload is the Microwave Imaging Radiometer using Aperture Synthesis. As part of comprehensive calibration and validation activities, several ground-based L-band radiometers, so-called ETH L-Band radiometers for soil moisture research (ELBARA-II), have been deployed. In this paper, we analyze a comprehensive set of measurements from one ELBARA-II deployment site in the northern boreal forest zone. The focus of this paper is in the detection of the evolution of soil frost (a relevant topic, e.g., for the study of carbon and methane cycles at high latitudes). We investigate the effects that soil freeze/thaw processes have on the L-band signature and present a simple modeling approach to analyze the relation between frost depth and the observed brightness temperature. Airborne observations are used to expand the analysis for different land cover types. Finally, the first SMOS observations from the same period are analyzed. Results show that soil freezing and thawing processes have an observable effect on the L-band signature of soil. Furthermore, the presented emission model is able to relate the observed dynamics in brightness temperature to the increase of soil frost.
    IEEE Transactions on Geoscience and Remote Sensing 01/2012; · 3.47 Impact Factor
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    ABSTRACT: In this paper we present the scientific objectives of the FLEX mission and the underlying rationale. It sketches the basic ideas of the new measurement concept, which is making use of the tandem configuration of FLEX with GMES/Sentinel-3, and outlines the most important instrument and system requirements. We will describe the envisaged instrument configuration that is in line with the measurement objectives, and which is supported by the latest results of the scientific investigations.
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
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    ABSTRACT: This study investigates the temporal behavior of the gravimetric vegetation water content (Mg) derived from SMOS (L-band) optical depth (τ) values. The analysis is done for the year 2010 over a coniferous forest site in the U.S. Resulting values of Mg are compared to values of leaf water potential obtained with the Soil-Plant-Atmosphere model and in situ data. A significant nonlinear correlation is found between the two (R=0.72, p
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
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    ABSTRACT: The SMOS Level-2 Processor is an operational routine to calculate the SMOS Level-2 product soil moisture from the radiometer brightness temperature (Tb). But, the radiative transfer from measured Tb into soil moisture is influenced by several conditions such as soil surface roughness and vegetation opacity, which are parameterized in a general way only. Surface soil roughness and vegetation opacity cannot be easily measured at the scale of SMOS observation of 30 - 50 km. The absolute values of these parameters for different land surfaces are uncertain, and the degree of this uncertainty is unknown as well. In addition, recent studies found that SMOS overestimates the Tb. In this paper, we present a method to enhance the accuracy of the SMOS soil moisture product by parameter estimation using a data assimilation technique (Sampling Importance Resampling Particle Filter - SIR-PF) with in situ soil moisture observations. Therefore, we developed an approach to analyze the ability of the system to track the temporal evolution of parameters such as vegetation opacity and soil surface roughness. Based on observed soil moisture and soil temperature, the L-MEB forward model was run and perturbed according to the measurement accuracy. L-MEB was integrated into a data assimilation framework using the SIR-PF, which is able to concurrently update L-MEB states and parameters. In addition, we investigate the ability of the proposed approach to account for the SMOS observation bias by introducing a bias factor in L-MEB. The overall advantage of the proposed sequential approach is its ability to be integrated into the operational near real time processing of the Level-2 product. The objectives of this study are: (i) to retrieve radiative transfer parameters and their temporal changes and (ii) to account for a bias and uncertainty in SMOS measurements.
    AGU Fall Meeting Abstracts. 12/2011;
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    ABSTRACT: In this article, we describe a technique to determine dry snow grain size from optical observations. The method is based on analysis of the snow reflectance in the near-infrared region, in particular, the Medium Resolution Imaging Spectrometer (MERIS) band at 865 nm, which is common to many spaceborne optical sensors, is used. In addition, the algorithm is applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) 1240 nm band. It is found that bands located at 1020 and 1240 nm are the most suitable for snow grain size remote-sensing applications. The developed method is validated using MODIS observations over flat snow deposited on a lake ice in Hokkaido, Japan.
    International Journal of Remote Sensing 11/2011; 32(22):6975-7008. · 1.36 Impact Factor

Publication Stats

759 Citations
73.29 Total Impact Points

Institutions

  • 2003–2013
    • European Center For Medium Range Weather Forecasts
      Shinfield, England, United Kingdom
  • 1999–2000
    • Princeton University
      • • Department of Civil and Environmental Engineering
      • • Department of Operations Research and Financial Engineering
      Princeton, NJ, United States