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In this paper, the miniaturization performance of waveguide bandpass filters loaded with three different periodic metallic metasurfaces is studied. The effective refractive index of holey structure, pin-loaded holes, and glide-symmetric metallic pins and their effects on the compactness of K/Ka band filters are investigated. In the glide-symmetric filter, a fourth-degree Chebyshev response with the center frequency of 28 GHz, bandwidth of 3 GHz, return loss of 20 dB, insertion loss of 0.4 dB, and the size reduction of 41.3% is achieved., QC 20230613

A 40-year-old previously healthy, non-atopic woman was referred for evaluation of a possible immunodeficiency disorder in the setting of an unusual erosive cheilitis and history of recurrent methicillin-resistant Staphylococcus aureus (MRSA) infection. Extensive work-up was non-diagnostic, including screening for immunologic disorders. She had failed multiple therapeutic modalities, including corticosteroid and immunosuppressive therapy. Tissue biopsy from the lip proved pivotal in demonstrating changes suggestive of factitial disease. This led to further detailed history-taking, yielding evidence of considerable psychologic distress. The patient was diagnosed with exfoliative cheilitis related to factitial disease in association with underlying untreated anxiety and psychologic trauma.

A 40-year-old previously healthy, non-atopic woman was referred for evaluation of a possible immunodeficiency disorder in the setting of an unusual erosive cheilitis and history of recurrent methicillin-resistant Staphylococcus aureus (MRSA) infection. Extensive work-up was non-diagnostic, including screening for immunologic disorders. She had failed multiple therapeutic modalities, including corticosteroid and immunosuppressive therapy. Tissue biopsy from the lip proved pivotal in demonstrating changes suggestive of factitial disease. This led to further detailed history-taking, yielding evidence of considerable psychologic distress. The patient was diagnosed with exfoliative cheilitis related to factitial disease in association with underlying untreated anxiety and psychologic trauma.

Using colloidal iron oxide nanoparticles with organic ligands, anchored in a separate step from the supports, has been shown to be beneficial to obtain homogeneously distributed metal particles with a narrow size distribution. Literature indicates that promoting these particles with sodium and sulfur creates an active Fischer-Tropsch catalyst to produce olefins, while further adding an H-ZSM-5 zeolite is an effective way to obtain aromatics. This research focused on the promotion of iron oxide colloids with sodium and sulfur using an inorganic ligand exchange followed by the attachment to H-ZSM-5 zeolite crystals. The catalyst referred to as FeP/Z, which consists of iron particles with inorganic ligands attached to a H-ZSM-5 catalyst, was compared to an unpromoted Fe/Z catalyst and an Fe/Z-P catalyst, containing the colloidal nanoparticles with organic ligands, promoted after attachment. A low CO conversion was observed on both FeP/Z and Fe/Z-P, originating from an overpromotion effect for both catalysts. However, when both promoted catalysts were washed (FeP/Z-W and Fe/Z-P-W) to remove the excess of promoters, the activity was much higher. Fe/Z-P-W simultaneously achieved low selectivity toward methane as part of the promoters were still present after washing, whereas for FeP/Z-W the majority of promoters was removed upon washing, which increased the methane selectivity. Moreover, due to the addition of Na+S promoters, the iron nanoparticles in the FeP/Z(-W) catalysts had grown considerably during catalysis, while those in Fe/Z-P(-W) and Fe/Z(-W) remained relatively stable. Lastly, as a large broadening of particle sizes for the used FeP/Z-W was found, where particle sizes had both increased and decreased, Ostwald ripening is suggested for particle growth accelerated by the presence of the promoters.

200 jaar geleden (in 1818) werd Friedrich Wilhelm Raiffeisen geboren. Hij zou uitgroeien tot een man die met zijn bescheiden maar doorwrochte koerswijziging in het denken én doen van mensen een grote invloed heeft op de grote en de kleine geschiedenis. We ontmoetten zijn ondernemersgeest in een eenvoudig dorpscafé. Stel dat we hem nog vragen zouden kunnen stellen. Hoe zou hij antwoorden?

In een razendsnel veranderende wereld zoekt ‘het coöperatieve’ naar nieuwe uitingsvormen. De betrokkenheid van leden, de legitimatie bij stakeholders, de aantrekkingskracht op nieuwe generaties. In de praktijk werken coöperaties dagelijks in dit spanningsveld. “Wetenschap kan bijdragen aan een beter begrip van de veranderingen, de achterliggende ontwikkelingen en de verhalen die we elkaar daarover vertellen”, aldus Professor Fulton. De Canadese hoogleraar (University of Saskatchewan) is keynotespeaker tijdens het NCR Business Event op 4 juli aanstaande.

Contains fulltext : 178589.pdf (publisher's version ) (Closed access)

Contains fulltext : 178589.pdf (publisher's version ) (Closed access)

Contains fulltext : 178589.pdf (publisher's version ) (Closed access)

‘Rond de tafel’ praten we deze keer over zelfevaluatie. Hoe vaak gebeurt het? Hoe gebeurt het? Wel of niet met een externe? Wel of niet voorafgegaan door een online-vragenlijst?

Het NCR-Ledenbetrokkenheidsonderzoek kreeg met de thesis van WUR-studente Nicole Sloot een verstevigd fundament. Internationale inzichten uit coöperatie- en marketingonderzoek verstevigden de basis en verdiepten de vraagstelling. In de toekomst kunnen nog nauwkeuriger uitspraken over ledenbetrokkenheid bij coöperaties worden gedaan. Zodoende kan de coöperatie effectiever werken aan wederzijdse betrokkenheid. Dit is mede nodig gezien de huidige ‘Zeitgeist’.

The accuracy of state-of-the-art global barotropic tide models is assessed using bottom pressure data, coastal tide gauges, satellite altimetry, various geodetic data on Antarctic ice shelves, and independent tracked satellite orbit perturbations. Tide models under review include empirical, purely hydrodynamic (forward), and assimilative dynamical, i.e., constrained by observations. Ten dominant tidal constituents in the diurnal, semidiurnal, and quarter-diurnal bands are considered. Since the last major model comparison project in 1997, models have improved markedly, especially in shallow-water regions and also in the deep ocean. The root-sum-square differences between tide observations and the best models for eight major constituents are approximately 0.9, 5.0, and 6.5 cm for pelagic, shelf, and coastal conditions, respectively. Large intermodel discrepancies occur in high latitudes, but testing in those regions is impeded by the paucity of high-quality in situ tide records. Long-wavelength components of models tested by analyzing satellite laser ranging measurements suggest that several models are comparably accurate for use in precise orbit determination, but analyses of GRACE intersatellite ranging data show that all models are still imperfect on basin and subbasin scales, especially near Antarctica. For the M2 constituent, errors in purely hydrodynamic models are now almost comparable to the 1980-era Schwiderski empirical solution, indicating marked advancement in dynamical modeling. Assessing model accuracy using tidal currents remains problematic owing to uncertainties in in situ current meter estimates and the inability to isolate the barotropic mode. Velocity tests against both acoustic tomography and current meters do confirm that assimilative models perform better than purely hydrodynamic models., Published in Reviews of Geophysics, v52 p243-282, 2014. The original document contains color images.

Contains fulltext : 136235.pdf (publisher's version ) (Open Access), Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

Contains fulltext : 136235.pdf (publisher's version ) (Open Access), Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

Contains fulltext : 136235.pdf (publisher's version ) (Open Access), Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

The accuracy of state-of-the-art global barotropic tide models is assessed using bottom pressure data, coastal tide gauges, satellite altimetry, various geodetic data on Antarctic ice shelves, and independent tracked satellite orbit perturbations. Tide models under review include empirical, purely hydrodynamic ("forward"), and assimilative dynamical, i.e., constrained by observations. Ten dominant tidal constituents in the diurnal, semidiurnal, and quarter-diurnal bands are considered. Since the last major model comparison project in 1997, models have improved markedly, especially in shallow-water regions and also in the deep ocean. The root-sum-square differences between tide observations and the best models for eight major constituents are approximately 0.9, 5.0, and 6.5 cm for pelagic, shelf, and coastal conditions, respectively. Large intermodel discrepancies occur in high latitudes, but testing in those regions is impeded by the paucity of high-quality in situ tide records. Long-wavelength components of models tested by analyzing satellite laser ranging measurements suggest that several models are comparably accurate for use in precise orbit determination, but analyses of GRACE intersatellite ranging data show that all models are still imperfect on basin and subbasin scales, especially near Antarctica. For the M-2 constituent, errors in purely hydrodynamic models are now almost comparable to the 1980-era Schwiderski empirical solution, indicating marked advancement in dynamical modeling. Assessing model accuracy using tidal currents remains problematic owing to uncertainties in in situ current meter estimates and the inability to isolate the barotropic mode. Velocity tests against both acoustic tomography and current meters do confirm that assimilative models perform better than purely hydrodynamic models.

The accuracy of state-of-the-art global barotropic tide models is assessed using bottom pressure data, coastal tide gauges, satellite altimetry, various geodetic data on Antarctic ice shelves, and independent tracked satellite orbit perturbations. Tide models under review include empirical, purely hydrodynamic ("forward"), and assimilative dynamical, i.e., constrained by observations. Ten dominant tidal constituents in the diurnal, semidiurnal, and quarter-diurnal bands are considered. Since the last major model comparison project in 1997, models have improved markedly, especially in shallow-water regions and also in the deep ocean. The root-sum-square differences between tide observations and the best models for eight major constituents are approximately 0.9, 5.0, and 6.5 cm for pelagic, shelf, and coastal conditions, respectively. Large intermodel discrepancies occur in high latitudes, but testing in those regions is impeded by the paucity of high-quality in situ tide records. Long-wavelength components of models tested by analyzing satellite laser ranging measurements suggest that several models are comparably accurate for use in precise orbit determination, but analyses of GRACE intersatellite ranging data show that all models are still imperfect on basin and subbasin scales, especially near Antarctica. For the M-2 constituent, errors in purely hydrodynamic models are now almost comparable to the 1980-era Schwiderski empirical solution, indicating marked advancement in dynamical modeling. Assessing model accuracy using tidal currents remains problematic owing to uncertainties in in situ current meter estimates and the inability to isolate the barotropic mode. Velocity tests against both acoustic tomography and current meters do confirm that assimilative models perform better than purely hydrodynamic models.

Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

We aim at the determination of the absolute, but temporally changing ocean circulation flow field and of associated mass and heat transports. The study is based on a state‐of‐the‐art circulation model assimilating the dynamic ocean topography (DOT) derived geodetically by subtracting the geoid from sea surface heights observed by satellite altimetry. Our geoid model is based on a satellite‐only combination of GRACE and GOCE. A prerequisite for the generation of the DOT and its assimilation is a spectral consistency between altimetric data and gravity field. Two different filter strategies were investigated, a global approach performed in the spectral domain and a track‐wise approach partly realized in the space domain. Further, error propagation needs to be performed to ensure optimal information content of the measured data. Our analysis focuses on the Southern Ocean and especially the Weddell Gyre, a region of high variability but also of poor data quality due to the presence of seasonal sea ice cover. Results are presented for different spatial resolutions and the impact of assimilating the geodetic DOT on the shape of the modelled Weddell Gyre, oceanic fronts and deeper ocean is discussed.

With the focus on the Southern Ocean, results of the assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into a finite element ocean model are investigated. We use the geodetic method to obtain the dynamical ocean topography from only the satellite measurements and an ensemble Kalman filter approach for assimilation of this data set into the finite element ocean model. The data assimilation scheme corrects all the ocean fields, although only the geodetic DOT is assimilated. Properties of the data assimilation algorithm, particularly with respect to the resolution of the data, are discussed in detail. By assimilating only absolute dynamical topography data, we were able to improve the model fields. The results of the assimilation agree better with observations which were not used for assimilation and lie outside the area covered by the altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in the Weddell Sea area at 800 m depth derived from Argo composite). In addition we show that the ocean model representation of the location of the fronts in the Southern Ocean is improved.

We use the geodetic method to obtain the dynamical ocean topography (DOT). This method combines the multi-mission-altimeter sea surface height and the GRACE/GOCE gravity field. Using the new global filtering approach, the spectral consistency of both fields is achieved by filtering the sea surface height and the geoid. The new global filtering approach reduces the artificats near the coast lines. Further, results of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into the finite element ocean model (FEOM) are investigated. By assimilating only absolute dynamical topography data using the ensemble Kalman filter and time varying observation error covariances, we were able to improve modeled fields. Results are closer to observations which were not used for assimilation and lie outside the area covered by altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in theWeddell Sea area.)

With the focus on the Southern Ocean circulation, results of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into the finite element ocean model (FEOM) are investigated. We use the geodetic method to obtain the dynamical ocean topography (DOT). This method combines the multi-mission-altimeter sea surface height and the GRACE/GOCE gravity field. Using the profile approach, the spectral consistency of both fields is achieved by filtering the sea surface height and the geoid. By combining the GRACE and GOCE data, a considerably shorter filter length can be used, which results in more DOT details. We show that this increase in resolution of measured DOT carries onto the results of data assimilation for the surface data. By assimilating only absolute dynamical topography data using the ensemble Kalman filter, we were able to improve modeled fields. Results are closer to observations which were not used for assimilation and lie outside the area covered by altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in the Weddell Sea area at 800 m depth derived from Argo composite.)

We aim at the determination of the absolute, but temporally changing ocean circulation flow field and of associated mass and heat transports. The study is based on a state‐of‐the‐art circulation model assimilating the dynamic ocean topography (DOT) derived geodetically by subtracting the geoid from sea surface heights observed by satellite altimetry. Our geoid model is based on a satellite‐only combination of GRACE and GOCE. A prerequisite for the generation of the DOT and its assimilation is a spectral consistency between altimetric data and gravity field. Two different filter strategies were investigated, a global approach performed in the spectral domain and a track‐wise approach partly realized in the space domain. Further, error propagation needs to be performed to ensure optimal information content of the measured data. Our analysis focuses on the Southern Ocean and especially the Weddell Gyre, a region of high variability but also of poor data quality due to the presence of seasonal sea ice cover. Results are presented for different spatial resolutions and the impact of assimilating the geodetic DOT on the shape of the modelled Weddell Gyre, oceanic fronts and deeper ocean is discussed.

We use the geodetic method to obtain the dynamical ocean topography (DOT). This method combines the multi-mission-altimeter sea surface height and the GRACE/GOCE gravity field. Using the new global filtering approach, the spectral consistency of both fields is achieved by filtering the sea surface height and the geoid. The new global filtering approach reduces the artificats near the coast lines. Further, results of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into the finite element ocean model (FEOM) are investigated. By assimilating only absolute dynamical topography data using the ensemble Kalman filter and time varying observation error covariances, we were able to improve modeled fields. Results are closer to observations which were not used for assimilation and lie outside the area covered by altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in theWeddell Sea area.)

With the focus on the Southern Ocean, results of the assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into a finite element ocean model are investigated. We use the geodetic method to obtain the dynamical ocean topography from only the satellite measurements and an ensemble Kalman filter approach for assimilation of this data set into the finite element ocean model. The data assimilation scheme corrects all the ocean fields, although only the geodetic DOT is assimilated. Properties of the data assimilation algorithm, particularly with respect to the resolution of the data, are discussed in detail. By assimilating only absolute dynamical topography data, we were able to improve the model fields. The results of the assimilation agree better with observations which were not used for assimilation and lie outside the area covered by the altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in the Weddell Sea area at 800 m depth derived from Argo composite). In addition we show that the ocean model representation of the location of the fronts in the Southern Ocean is improved.

With the focus on the Southern Ocean circulation, results of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity data into the finite element ocean model (FEOM) are investigated. We use the geodetic method to obtain the dynamical ocean topography (DOT). This method combines the multi-mission-altimeter sea surface height and the GRACE/GOCE gravity field. Using the profile approach, the spectral consistency of both fields is achieved by filtering the sea surface height and the geoid. By combining the GRACE and GOCE data, a considerably shorter filter length can be used, which results in more DOT details. We show that this increase in resolution of measured DOT carries onto the results of data assimilation for the surface data. By assimilating only absolute dynamical topography data using the ensemble Kalman filter, we were able to improve modeled fields. Results are closer to observations which were not used for assimilation and lie outside the area covered by altimetry in the Southern Ocean (e.g. temperature of surface drifters or deep temperatures in the Weddell Sea area at 800 m depth derived from Argo composite.)

In this work we examine the impact of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity fields into the finite element ocean model (FEOM), with the focus on the Southern Ocean circulation. In order to do so, we use the geodetic approach for obtaining the dynamical ocean topography (DOT), that combines the multi-mission-altimeter data and the GRACE/GOCE gravity fields, and requires that both fields be spectrally consistent. The spectral consistency is achieved by filtering of the sea surface height and the geoid using profile approach. Combining the GRACE and GOCE data, a considerably shorter filter length resolving more DOT details can be used. In order to specify the spectrally consistent geodetic DOT we applied the Jekeli-Wahr filter corresponding to 241 km, 121 km, 97 km and 81 km halfwidths for the GRACE/GOCE based gravity field model GOCO01S and to the sea surface. More realistic features of the ocean assimilation were obtained in the Weddel gyre area due to increased resolution of the data fields, particularly for temperature field at the 800 m depth compared to Argo data.

Estimation of ocean circulation is investigated via assimilation of satellite measurements of the dynamic ocean topography (DOT) into the global finite-element ocean model (FEOM). The DOT was obtained by means of a geodetic approach from carefully cross-calibrated multi-mission altimeter data and GRACE gravity fields. The spectral consistency was achieved by consistently filtering both, the sea surface and the geoid. The filter length is determined by the spatial resolution of the gravity field and corresponds to approximately 241 km half width for the GRACE-based gravity field model ITG-Grace03s. The assimilation of the geodetic DOT was performed by employing a local singular evolutive interpolated Kalman (SEIK) filter in combination with the method of weighting of observations. It is shown that this approach leads to a successful assimilation technique that reduced the RMS difference between the model and the data from 16 cm to 5 cm during one year of assimilation. The ocean model returns an optimized mean dynamic ocean topography. The effects of assimilation on transport estimates across several hydrographic World Ocean Circulation Experiment (WOCE) sections show improvements compared to the FEOM run without data assimilation. As a result of the assimilation, DOT estimates are available in the polar or coastal regions where the geodetic estimates from satellite data alone are not adequate. Furthermore, more realistic features of the ocean can be seen in these areas compared to those obtained using the filtered data fields.

In this work we examine the impact of assimilation of multi-mission-altimeter data and the GRACE/GOCE gravity fields into the finite element ocean model (FEOM), with the focus on the Southern Ocean circulation. In order to do so, we use the geodetic approach for obtaining the dynamical ocean topography (DOT), that combines the multi-mission-altimeter data and the GRACE/GOCE gravity fields, and requires that both fields be spectrally consistent. The spectral consistency is achieved by filtering of the sea surface height and the geoid using profile approach. Combining the GRACE and GOCE data, a considerably shorter filter length resolving more DOT details can be used. In order to specify the spectrally consistent geodetic DOT we applied the Jekeli-Wahr filter corresponding to 241 km, 121 km, 97 km and 81 km halfwidths for the GRACE/GOCE based gravity field model GOCO01S and to the sea surface. More realistic features of the ocean assimilation were obtained in the Weddel gyre area due to increased resolution of the data fields, particularly for temperature field at the 800 m depth compared to Argo data.

Estimation of ocean circulation is investigated via assimilation of satellite measurements of the dynamic ocean topography (DOT) into the global finite-element ocean model (FEOM). The DOT was obtained by means of a geodetic approach from carefully cross-calibrated multi-mission altimeter data and GRACE gravity fields. The spectral consistency was achieved by consistently filtering both, the sea surface and the geoid. The filter length is determined by the spatial resolution of the gravity field and corresponds to approximately 241 km half width for the GRACE-based gravity field model ITG-Grace03s. The assimilation of the geodetic DOT was performed by employing a local singular evolutive interpolated Kalman (SEIK) filter in combination with the method of weighting of observations. It is shown that this approach leads to a successful assimilation technique that reduced the RMS difference between the model and the data from 16 cm to 5 cm during one year of assimilation. The ocean model returns an optimized mean dynamic ocean topography. The effects of assimilation on transport estimates across several hydrographic World Ocean Circulation Experiment (WOCE) sections show improvements compared to the FEOM run without data assimilation. As a result of the assimilation, DOT estimates are available in the polar or coastal regions where the geodetic estimates from satellite data alone are not adequate. Furthermore, more realistic features of the ocean can be seen in these areas compared to those obtained using the filtered data fields.