The TIGGE project and its achievements

TIGGE was a major component of the THORPEX (The Observing System Research and Predictability Experiment) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics. The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a Multi-model Grand Ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed. TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world, and are a focus of multi-model ensemble research. Their extra-tropical transition also has a major impact on skill of mid-latitude forecasts. We also review how TIGGE has added to our understanding of the dynamics of extra-tropical cyclones and storm tracks. Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. Finally the paper considers the legacy of TIGGE. We discuss the priorities and key issues in predictability and ensemble forecasting, including the new opportunities of convective-scale ensembles, links with ensemble data assimilation methods, and extension of the range of useful forecast skill

The role of feedback quality and organizational cynicism for affective commitment through leader-member exchange

Contains fulltext : 239160.pdf (Publisher’s version ) (Closed access)28 mei 202023 p

Ressourcen nutzen - Möglichkeiten erweitern : interuniversitäre Kooperation im Netzwerk Bildungswissenschaften

Die aktuellen Reformprozesse an deutschen Hochschulen stellen nicht nur für die Studierenden eine Herausforderung bezüglich der Studienplanung dar, sondern auch für die Lehrenden, die auf Veranstaltungsebene mit der verstärkt geforderten Orientierung an berufspraktischen Kompetenzen konfrontiert werden. Im Rahmen des lehramtsspezifischen Projekts „Netzwerk Bildungswissenschaften“ wird diesen Forderungen durch die Entwicklung und Erprobung flexibel nutzbarer Lehr-/Lern-angebote begegnet, die darüber hinaus standortunabhängig eingesetzt werden können. Die im Verlauf des Projekts identifizierten Problembereiche beim Angebotsaustausch werden im folgenden Beitrag beschrieben, wobei ein besonderer Fokus auf die dazu entwickelten Lösungsansätze gelegt wird. 23.03.2010 | Petra Bauer (Mainz), Christian Bogner (Kaiserslautern), Eva Kleß (Landau), Christine Menzer (Kaiserslautern), Anke Pfeiffer (Koblenz) & Tim Thielen (Trier

Measuring water affordability in developed economies : the added value of a needs-based approach

In developed countries, water affordability problems remain up on the agenda as the increasing financial costs of water services can impede the realisation of an equal access to water. More than ever, public authorities that define water tariffs face the challenge of reconciling environmental and cost recovery objectives with equity and financial accessibility for all. Indicators of water affordability can be helpful in this regard. Conventional affordability indicators often rely on the actual amount that households spend on water use. In contrast, we propose a needs-based indicator that measures the risk of being unable to afford the amount of water necessary to fulfill essential needs, i.e. needs that should be fulfilled for adequate participation in society. In this paper we set forth the methodological choices inherent to constructing a needs-based affordability indicator. Using a micro-dataset on households in Flanders (Belgium), we compare its results with the outcomes of a more common actual expenses-indicator. The paper illustrates how the constructed needs-based indicator can complement existing affordability indicators, and its capacity to reveal important risk groups

An improved diagnostic tool to predict cartilage formation in an osteoarthritic joint environment

Osteoarthritis (OA) is a degenerative joint disease with progressive articular cartilage loss. Due to the chondrogenic potential of human mesenchymal stromal cells (MSCs), MSC-based therapies are promising treatment strategies for cartilage loss. However, the local joint microenvironment has a great impact on the success of cartilage formation by MSCs. This local joint environment is different between patients and therefore the outcome of MSC therapies is uncertain. We previously developed gene promoter-based reporter assays as a novel tool to predict the effect of a patient's OA joint microenvironment on the success of MSC-based cartilage formation. Here we describe an improved version of this molecular tool with increased prediction accuracy. For this, we generated fourteen stable cell lines using transcription factor (TF) binding elements (AP1, ARE, CRE, GRE, ISRE, NFAT5, NFκB, PPRE, SBE, SIE, SOX9, SRE, SRF, TCF/LEF) to drive luciferase reporter gene expression, and evaluated the cell lines for their responsiveness to an osteoarthritic microenvironment by stimulation with OA synovium-conditioned medium (OAs-cm; n=31). To study the effect of this OA microenvironment on MSC-based cartilage formation, MSCs were cultured in a three-dimensional pellet culture model while stimulated with OAs-cm. Cartilage formation was assessed histologically and by quantifying sulfated glycosaminoglycan (sGAG) production. Six TF reporters correlated significantly with the effect of OAs-cm on cartilage formation. We validated the predictive value of these TF reporters with an independent cohort of OAs-cm (n=22) and compared the prediction accuracy between our previous and the current new tool. Furthermore, we investigated which combination of reporters could predict the effect of the OA microenvironment on cartilage repair with the highest accuracy. A combination between the TF (NFκB) and the promoter-based (IL6) reporter proved to reach a more accurate prediction compared to the tools separately. These developments are an important step towards a diagnostic tool that can be used for personalized cartilage repair strategies for OA patients

An improved diagnostic tool to predict cartilage formation in an osteoarthritic joint environment

Osteoarthritis (OA) is a degenerative joint disease with progressive articular cartilage loss. Due to the chondrogenic potential of human mesenchymal stromal cells (MSCs), MSC-based therapies are promising treatment strategies for cartilage loss. However, the local joint microenvironment has a great impact on the success of cartilage formation by MSCs. This local joint environment is different between patients and therefore the outcome of MSC therapies is uncertain. We previously developed gene promoter-based reporter assays as a novel tool to predict the effect of a patient's OA joint microenvironment on the success of MSC-based cartilage formation. Here we describe an improved version of this molecular tool with increased prediction accuracy. For this, we generated fourteen stable cell lines using transcription factor (TF) binding elements (AP1, ARE, CRE, GRE, ISRE, NFAT5, NFκB, PPRE, SBE, SIE, SOX9, SRE, SRF, TCF/LEF) to drive luciferase reporter gene expression, and evaluated the cell lines for their responsiveness to an osteoarthritic microenvironment by stimulation with OA synovium-conditioned medium (OAs-cm; n=31). To study the effect of this OA microenvironment on MSC-based cartilage formation, MSCs were cultured in a three-dimensional pellet culture model while stimulated with OAs-cm. Cartilage formation was assessed histologically and by quantifying sulfated glycosaminoglycan (sGAG) production. Six TF reporters correlated significantly with the effect of OAs-cm on cartilage formation. We validated the predictive value of these TF reporters with an independent cohort of OAs-cm (n=22) and compared the prediction accuracy between our previous and the current new tool. Furthermore, we investigated which combination of reporters could predict the effect of the OA microenvironment on cartilage repair with the highest accuracy. A combination between the TF (NFκB) and the promoter-based (IL6) reporter proved to reach a more accurate prediction compared to the tools separately. These developments are an important step towards a diagnostic tool that can be used for personalized cartilage repair strategies for OA patients