Valuing information from mesoscale forecasts

The development of meso-gamma scale numerical weather prediction (NWP) models requires a substantial investment in research, development and computational resources. Traditional objective verification of deterministic model output fails to demonstrate the added value of high-resolution forecasts made by such models. It is generally accepted from subjective verification that these models nevertheless have a predictive potential for small-scale weather phenomena and extreme weather events. This has prompted an extensive body of research into new verification techniques and scores aimed at developing mesoscale performance measures that objectively demonstrate the return on investment in meso-gamma NWP. In this article it is argued that the evaluation of the information in mesoscale forecasts should be essentially connected to the method that is used to extract this information from the direct model output (DMO). This could be an evaluation by a forecaster, but, given the probabilistic nature of small-scale weather, is more likely a form of statistical post-processing. Using model output statistics (MOS) and traditional verification scores, the potential of this approach is demonstrated both on an educational abstraction and a real world example. The MOS approach for this article incorporates concepts from fuzzy verification. This MOS approach objectively weighs different forecast quality measures and as such it is an essential extension of fuzzy methods

Towards LLOD-based language contact studies: a case study in interoperability

We describe a methodological and technical framework for conducting qualitative and quantitative studies of linguistic research questions over diverse and heterogeneous data sources such as corpora and elicitations. We demonstrate how LLOD formalisms can be employed to develop extraction pipelines for features and linguistic examples from corpora and collections of interlinear glossed text, and furthermore, how SPARQL UPDATE can be employed (1) to normalize diverse data against a reference data model (here, POWLA), (2) to harmonize annotation vocabularies by reference to terminology repositories (here, OLiA), (3) to extract examples from these normalized data structures regardless of their origin, and (4) to implement this extraction routine in a tool-independent manner for different languages with different annotation schemes. We demonstrate our approach for language contact studies for genetically unrelated, but neighboring languages from the Caucasus area, Eastern Armenian and Georgian

Universal morphologies for the Caucasus region

The Caucasus region is famed for its rich and diverse arrays of languages and language families, often challenging European-centered views established in traditional linguistics. In this paper, we describe ongoing efforts to improve the coverage of Universal Morphologies for languages of the Caucasus region. The Universal Morphologies (UniMorph) are a recent community project aiming to complement the Universal Dependencies which focus on morphosyntax and syntax. We describe the development of UniMorph resources for Nakh-Daghestanian and Kartvelian languages as a well as for Classical Armenian, we discuss challenges that the complex morphology of these and related languages poses to the current design of UniMorph, and suggest possibilities to improve the applicability of UniMorph for languages of the Caucasus region in particular and for low resource languages in general. We also criticize the UniMorph TSV format for its limited expressiveness, and suggest to complement the existing UniMorph workflow with support for additional source formats on grounds of Linked Open Data technology

Urban climate services : climate impact projections and their uncertainties at city scale

In many cities across Europe, both urban authorities and private actors have made strong commitments to adapt to future climate changes. Although a lot of climate information is available at the global and regional scale, this is often not the case at the local urban scale. Moreover, such information should account for a wide range of uncertainty factors ranging from global to city-scale development scenarios to uncertainties due to model errors. In an effort to lay the methodological groundworks for reliable urban climate services, URCLIM explores a compound handling of these uncertainties for various European cities and applies it to the assessment of adaptation measures

The impact of climate change on the critical weather conditions at Schiphol airport (Impact)

Schiphol is van groot belang voor de economische positie van Nederland. De luchthaven is erg gevoelig voor kritieke weersomstandigheden zoals mist, intensieve neerslag en hevige wind. Als gevolg van klimaatverandering verwachten we dat ook de variabiliteit van het weer op de luchthaven en de frequentie en intensiteit van kritieke weersomstandigheden zullen veranderen, maar een precieze kwantificering daarvan ontbreekt. De belangrijkste doelstelling van dit project is daarom het verstrekken en demonstreren van het volgende generatie weer‐ en klimaatmodel HARMONIE. Dit is een nieuw model dat beter geschikt lijkt om het effect van klimaatverandering op lokale kritieke weersomstandigheden op de luchthaven te kwantificeren en te begrijpen. Bovendien zal kennis uit dit project worden gebruikt om de kwaliteit van onze huidige en toekomstige weersvoorspellingen te verbeteren. In dit project wordt het potentieel van het HARMONIE model, om meer gedetailleerdere en nauwkeurigere weersvoorspellingen voor luchthaven Schiphol te leveren dan ons huidige operationele weermodel HIRLAM, nagegaan in het huidige klimaat

Methodology for obtaining wind gusts using Doppler lidar

A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable with those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available. This novel method also provides estimates for wind gusts at arbitrary gust durations, including those shorter than the temporal resolution of the Doppler lidar measurements. The input parameters for the scaling method are the measured wind-gust speed as well as the mean and standard deviation of the horizontal wind speed. The method was tested using WindCube V2 Doppler lidar measurements taken next to a 100 m high meteorological mast. It is shown that the method can provide realistic Doppler lidar estimates of the gust factor, i.e. the ratio of the wind-gust speed to the mean wind speed. The method reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03 and can be improved further to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving-averaged) horizontal wind speed. To assure the data quality in this study, we applied a filtering technique based on spike detection to remove possible outliers in the Doppler lidar data. We found that the spike detection-removal method clearly improved the wind-gust measurements, both with and without the scaling method. Spike detection also outperformed the traditional Doppler lidar quality assurance method based on carrier-to-noise ratio, by removing additional unrealistic outliers present in the time serie

Human and murine fibroblast single cell transcriptomics reveals fibroblast clusters are differentially affected by ageing, and serum cholesterol

Aims Specific fibroblast markers and in-depth heterogeneity analysis are currently lacking, hindering functional studies in cardiovascular diseases (CVDs). Here, we established cell-type markers and heterogeneity in murine and human arteries and studied the adventitial fibroblast response to CVD and its risk factors hypercholesterolaemia and ageing. Methods and results Murine aorta single-cell RNA-sequencing analysis of adventitial mesenchymal cells identified fibroblast-specific markers. Immunohistochemistry and flow cytometry validated platelet-derived growth factor receptor alpha (PDGFRA) and dipeptidase 1 (DPEP1) across human and murine aorta, carotid, and femoral arteries, whereas traditional markers such as the cluster of differentiation (CD)90 and vimentin also marked transgelin+ vascular smooth muscle cells. Next, pseudotime analysis showed multiple fibroblast clusters differentiating along trajectories. Three trajectories, marked by CD55 (Cd55+), Cxcl chemokine 14 (Cxcl14+), and lysyl oxidase (Lox+), were reproduced in an independent RNA-seq dataset. Gene ontology (GO) analysis showed divergent functional profiles of the three trajectories, related to vascular development, antigen presentation, and/or collagen fibril organization, respectively. Trajectory-specific genes included significantly more genes with known genome-wide associations (GWAS) to CVD than expected by chance, implying a role in CVD. Indeed, differential regulation of fibroblast clusters by CVD risk factors was shown in the adventitia of aged C57BL/6J mice, and mildly hypercholesterolaemic LDLR KO mice on chow by flow cytometry. The expansion of collagen-related CXCL14+ and LOX+ fibroblasts in aged and hypercholesterolaemic aortic adventitia, respectively, coincided with increased adventitial collagen. Immunohistochemistry, bulk, and single-cell transcriptomics of human carotid and aorta specimens emphasized translational value as CD55+, CXCL14+ and LOX+ fibroblasts were observed in healthy and atherosclerotic specimens. Also, trajectory-specific gene sets are differentially correlated with human atherosclerotic plaque traits. Conclusion We provide two adventitial fibroblast-specific markers, PDGFRA and DPEP1, and demonstrate fibroblast heterogeneity in health and CVD in humans and mice. Biological relevance is evident from the regulation of fibroblast clusters by age and hypercholesterolaemia in vivo, associations with human atherosclerotic plaque traits, and enrichment of genes with a GWAS for CVD

Dynamic Construction of Generic Functions

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