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Modeling leading-edge erosion has been a challenging task due to its multidisciplinary nature involving several variables such as weather conditions, blade coating properties, and operational characteristics. While the process of wind turbine blade erosion is often described by engineering models that rely on the well-known Springer model, there is a glaring need for modeling approaches supported by field data. This paper presents a data-driven framework for modeling erosion damage based on blade inspections from several wind farms in northern Europe and mesoscale numerical weather prediction (NWP) models. The outcome of the framework is a machine-learning-based model that can be used to predict and/or forecast leading-edge erosion damage based on weather data/simulations and user-specified wind turbine characteristics. The model is based on feedforward artificial neural networks utilizing ensemble learning for robust training and validation. The model output fits directly into the damage terminology used by industry and can therefore support site-specific planning and scheduling of repairs as well as budgeting of operation and maintenance costs.

Purpose: The objective of this study was to test if combining antecedent systolic blood pressure (SBP) with traditional risk factors and hypertension-mediated organ damage (HMOD) improves risk stratification for subsequent cardiovascular disease. Materials and methods: 1910 subjects participated in this study. Antecedent SBP was defined as the average of measurements obtained in 1982 and in 1987. Current SBP was obtained in 1993. HMOD were examined in 1993. HMOD was defined as either atherosclerotic plaque(s), increased pulse wave velocity, increased urine albumin creatinine ratio (above the 90th percentile) or left ventricular hypertrophy. Major adverse cardiovascular events (MACE) including myocardial infarction, cerebrovascular disease, heart failure and arrhythmia were obtained from national registries. Results: Subjects were divided into two age categories: a middle-aged group (aged 41 or 51) and an older group (aged 61 or 71). From 1993 to 2010, 425 events were observed. In multivariable analysis with both current and antecedent SBP adjusted for traditional risk factors, current SBP was associated with each measure of HMOD whilst antecedent SBP was not significantly associated with urine albumin creatinine ratio in the older group, LVMI in the middle-aged group, or the presence of plaque in any of the age groups (all p > 0.15). When current and antecedent SBP were evaluated together, current SBP was not associated with MACE in the middle-aged subgroup [HR = 1.09 (0.96–1.22), p = 0.18] but remained associated with MACE in the older subgroup [HR = 1.21 (1.10–1.34), p

Urban development models typically provide simulated building areas in an aggregated form. When using such outputs to parametrize pluvial flood risk simulations in an urban setting, we need to identify ways to characterize imperviousness and flood exposure. We develop data-driven approaches for establishing this link, and we focus on the data resolutions and spatial scales that should be considered. We use regression models linking aggregated building areas to total imperviousness and models that link aggregated building areas and simulated flood areas to flood damage. The data resolutions used for training regression models are demonstrated to have a strong impact on identifiability, with too fine data resolutions preventing the identification of the link between building areas and hydrology and too coarse resolutions leading to uncertain parameter estimates. The optimal data resolution for modeling imperviousness was identified to be 400 m in our case study, while an aggregation of the data to at least 1000 m resolution is required when modeling flood damage. In addition, regression models for flood damage are more robust when considering building data with coarser resolutions of 200 m than with finer resolutions. The results suggest that aggregated building data can be used to derive realistic estimations of flood risk in screening simulations.

Background Although myocardial infarction (MI) and atrial fibrillation (AF) are frequent comorbidities and share common cardiovascular risk factors, the direction and strength of the association of the risk factors with disease onset, subsequent disease incidence, and mortality are not completely understood. Methods and Results In pooled multivariable Cox regression analyses, we examined temporal relations of disease onset and identified predictors of MI, AF, and all‐cause mortality in 108 363 individuals (median age, 46.0 years; 48.2% men) free of MI and AF at baseline from 6 European population‐based cohorts. During a maximum follow‐up of 10.0 years, 3558 (3.3%) individuals were diagnosed exclusively with MI, 1922 (1.8%) with AF but no MI, and 491 (0.5%) individuals developed both MI and AF. Association of sex, systolic blood pressure, antihypertensive treatment, and diabetes appeared to be stronger with incident MI than with AF, whereas increasing age and body mass index showed a higher risk for incident AF. Total cholesterol and daily smoking were significantly related to incident MI but not AF. Combined population attributable fraction of cardiovascular risk factors was >70% for incident MI, whereas it was only 27% for AF. Subsequent MI after AF (hazard ratio [HR], 1.68; 95% CI, 1.03–2.74) and subsequent AF after MI (HR, 1.75; 95% CI, 1.31–2.34) both significantly increased overall mortality risk. Conclusions We observed different associations of cardiovascular risk factors with both diseases indicating distinct pathophysiological pathways. Subsequent diagnoses of MI and AF significantly increased mortality risk.

Background The main aim was to examine age-specific risk factor associations with incident atrial fibrillation (AF) and their attributable fraction in a large European cohort. Additionally, we aimed to examine risk of stroke and mortality in relation to new-onset AF across age.Methods We used individual-level data (n=66 951, 49.1% men, age range 40–98 years at baseline) from five European cohorts of the MOnica Risk, Genetics, Archiving and Monograph Consortium. The participants were followed for incident AF for up to 10 years and the association with modifiable risk factors from the baseline examinations (body mass index (BMI), hypertension, diabetes, daily smoking, alcohol consumption and history of stroke and myocardial infarction (MI)) was examined. Additionally, the participants were followed up for incident stroke and all-cause mortality after new-onset AF.Results AF incidence increased from 0.9 per 1000 person-years at baseline age 40–49 years, to 17.7 at baseline age ≥70 years. Multivariable-adjusted Cox models showed that higher BMI, hypertension, high alcohol consumption and a history of stroke or MI were associated with increased risk of AF across age groups (p

In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) and ALADIN (Aire Limitée Adaptation Dynamique Développement International); and COSMO–EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU–GPU arrangements.

Abstract Background Probiosis is considered a potential strategy to reduce antibiotics use and prevent post-weaning diarrhea (PWD). This study investigated the effect of Bacillus amyloliquefaciens DSM25840 or Bacillus subtilis DSM25841 supplementation on growth, health, immunity, intestinal functionality and microbial profile of post-weaning pigs after enterotoxigenic E. coli (ETEC) F4 challenge. Methods Sixty-four post-weaning piglets (7748 g ± 643 g) were randomly allocated to four groups: control basal diet (CO); CO + 1.28 × 106 CFU/g of B. amyloliquefaciens (BAA); CO + 1.28 × 106 CFU/g feed of B. subtilis (BAS); CO + 1 g colistin/kg of feed (AB). At day (d) 7, animals were challenged with 105 CFU/mL of ETEC F4ac O149 and then followed for fecal score and performance until d 21. Blood was collected at d 6, d 12 and d 21 for immunoglobulins, at d 8 for acute phase proteins, at d 8 and d 21 for metabolomics analysis. Jejunum was sampled for morphometry, quantification of apoptosis, cell proliferation, neutral and acid mucine and IgA secretory cells, and microarray analysis at d 21. Jejunum and cecum contents were collected for microbiota at d 21. Results AB and BAS reduced the fecal score impairment compared to CO (P

Abstract Background The phyla Cnidaria, Placozoa, Ctenophora, and Porifera emerged before the split of proto- and deuterostome animals, about 600 million years ago. These early metazoans are interesting, because they can give us important information on the evolution of various tissues and organs, such as eyes and the nervous system. Generally, cnidarians have simple nervous systems, which use neuropeptides for their neurotransmission, but some cnidarian medusae belonging to the class Cubozoa (box jellyfishes) have advanced image-forming eyes, probably associated with a complex innervation. Here, we describe a new transcriptome database from the cubomedusa Tripedalia cystophora. Results Based on the combined use of the Illumina and PacBio sequencing technologies, we produced a highly contiguous transcriptome database from T. cystophora. We then developed a software program to discover neuropeptide preprohormones in this database. This script enabled us to annotate seven novel T. cystophora neuropeptide preprohormone cDNAs: One coding for 19 copies of a peptide with the structure pQWLRGRFamide; one coding for six copies of a different RFamide peptide; one coding for six copies of pQPPGVWamide; one coding for eight different neuropeptide copies with the C-terminal LWamide sequence; one coding for thirteen copies of a peptide with the RPRAamide C-terminus; one coding for four copies of a peptide with the C-terminal GRYamide sequence; and one coding for seven copies of a cyclic peptide, of which the most frequent one has the sequence CTGQMCWFRamide. We could also identify orthologs of these seven preprohormones in the cubozoans Alatina alata, Carybdea xaymacana, Chironex fleckeri, and Chiropsalmus quadrumanus. Furthermore, using TBLASTN screening, we could annotate four bursicon-like glycoprotein hormone subunits, five opsins, and 52 other family-A G protein-coupled receptors (GPCRs), which also included two leucine-rich repeats containing G protein-coupled receptors (LGRs) in T. cystophora. The two LGRs are potential receptors for the glycoprotein hormones, while the other GPCRs are candidate receptors for the above-mentioned neuropeptides. Conclusions By combining Illumina and PacBio sequencing technologies, we have produced a new high-quality de novo transcriptome assembly from T. cystophora that should be a valuable resource for identifying the neuronal components that are involved in vision and other behaviors in cubomedusae.

Background Differences in risk factors for atrial fibrillation (AF) and heart failure (HF) are incompletely understood. Aim of this study was to understand whether risk factors and biomarkers show different associations with incident AF and HF and to investigate predictors of subsequent onset and mortality. Methods and Results In N=58 693 individuals free of AF/HF from 5 population‐based European cohorts, Cox regressions were used to find predictors for AF, HF, subsequent onset, and mortality. Differences between associations were estimated using bootstrapping. Median follow‐up time was 13.8 years, with a mortality of 15.7%. AF and HF occurred in 5.0% and 5.4% of the participants, respectively, with 1.8% showing subsequent onset. Age, male sex, myocardial infarction, body mass index, and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) showed similar associations with both diseases. Antihypertensive medication and smoking were stronger predictors of HF than AF. Cholesterol, diabetes mellitus, and hsCRP (high‐sensitivity C‐reactive protein) were associated with HF, but not with AF. No variable was exclusively associated with AF. Population‐attributable risks were higher for HF (75.6%) than for AF (30.9%). Age, male sex, body mass index, diabetes mellitus, and NT‐proBNP were associated with subsequent onset, which was associated with the highest all‐cause mortality risk. Conclusions Common risk factors and biomarkers showed different associations with AF and HF, and explained a higher proportion of HF than AF risk. As the subsequent onset of both diseases was strongly associated with mortality, prevention needs to be rigorously addressed and remains challenging, as conventional risk factors explained only 31% of AF risk.

One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection can attract more settlements and high-value assets in the areas protected by the new measures. Other studies have explored how structural measures can generate a sense of complacency, which can act to reduce preparedness. These paradoxical risk changes have been described as levee effect, safe development paradox or safety dilemma. In this commentary, we briefly review this phenomenon by critically analysing the intended benefits and unintended effects of structural flood protection, and then we propose an interdisciplinary research agenda to uncover these paradoxical dynamics of risk.

The rate at which oral tobacco-derived nicotine (OTDN) and snus pouches release nicotine into saliva is crucial to determine product performance. As no standardized method is available for this purpose, this study sought to develop a biorelevant dissolution method that could both discriminate between different products and predict in vivo behavior. Using a μDISS Profiler™ as a surrogate for the US Pharmacopoeia standard apparatuses and a custom-made sinker, nicotine release from an OTDN pouch product (ZYN® Dry Smooth) and a snus product (General® Pouched Snus White Portion Large) was determined in biorelevant volumes (10 mL) of artificial saliva. In addition, nicotine extraction in vivo was measured for both products. Strikingly, the method showed distinct dissolution curves for OTDN and snus pouches, and the nicotine release observed in vitro did not significantly differ from the nicotine extracted in vivo. The custom-made sinker was designed to accommodate both loose and pouched oral tobacco/nicotine products, and thus the proposed in vitro dissolution method is suitable to assess nicotine release from OTDN and snus pouches. Apart from providing individual dissolution curves, the method was also able to predict in vivo nicotine extraction. Thus, this method could serve as a (biorelevant) monograph for product equivalence studies.

HARMONIE-AROME is a convection-permitting non-hydrostatic model that includes the multi-purpose SURFEX surface model. It is developed for high resolution (1–3 km) weather forecasting and applied in a number of regions in Europe and the Mediterranean. A version of HARMONIE-AROME is also under development for regional climate modelling. Here we run HARMONIE-AROME for a domain over Greenland that includes a significant portion of the Greenland ice sheet. The model output reproduces temperature, wind speed and direction and relative humidity over the ice sheet well when compared with the observations from PROMICE automatic weather stations (AWS) operated within the model domain on the ice sheet (mean temperature bias 1.31 ± 3.6 K) but we identified a much lower bias (−0.16 ± 2.3 K) at PROMICE sites on days where melt does not occur at the ice sheet surface and is thus an artefact of the simplified surface scheme over glaciers in the existing HARMONIE-AROME operational set-up. The bias in summer time temperature also affects wind speed and direction as the dominant katabatic winds are caused by the cold ice surface and slope gradient. By setting an upper threshold to the surface temperature of the ice surface within SURFEX we show that the weather forecast error over the Greenland ice sheet can be reduced in summer when glacier ice is exposed. This improvement will facilitate accurate ice melt and run-off computations, important both for ice surface mass budget estimation and for commercial applications such as hydro-power forecasting. Furthermore, the HCLIM regional climate model derived from HARMONIE-AROME will need to accurately account for glacier surface processes in these regions in order to be used to accurately compute the surface mass budget of ice sheets and glaciers, a key goal of regional climate modelling studies in Greenland.

In today's history museums, the past is communicated through many other means than original artefacts. This interdisciplinary and theoretical article suggests a new approach to studying the use of audio-visual media, such as film, video and related media types, in a museum context. The centre of interest is how history and authenticity is mediated at history museums and how museum visitors perceive this use. In this article, focus is moved away from technology and specific types of installations to concentrate on what museums do with technology. Building on disciplines such as media science and museum studies, existing case studies, and real life observations, the suggested framework instead stress particular characteristics of contextual use of audio-visual media in history museums, such as authenticity, virtuality, interativity, social context and spatial attributes of the communication design.

The Environment – High Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by the Danish Meteorological Institute (DMI) in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The model is based on the HIRLAM NWP model with online integrated pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and atmospheric composition feedbacks. To make the model suitable for chemical weather forecasting in urban areas, the meteorological part was improved by implementation of urban parameterisations. The dynamical core was improved by implementing a locally mass-conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The current version (7.2), in comparison with previous versions, has a more advanced and cost-efficient chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004, the Enviro-HIRLAM has been used for different studies, including operational pollen forecasting for Denmark since 2009 and operational forecasting atmospheric composition with downscaling for China since 2017. Following the main research and development strategy, further model developments will be extended towards the new NWP platform – HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.

The economic and human consequences of extreme precipitation and the related flooding of urban areas have increased rapidly over the past decades. Some of the key factors that affect the risks to urban areas include climate change, the densification of assets within cities and the general expansion of urban areas. In this paper, we examine and compare quantitatively the impact of climate change and recent urban development patterns on the exposure of four European cities to pluvial flooding. In particular, we investigate the degree to which pluvial floods of varying severity and in different geographical locations are influenced to the same extent by changes in urban land cover and climate change. We have selected the European cities of Odense, Vienna, Strasbourg and Nice for analyses to represent different climatic conditions, trends in urban development and topographical characteristics. We develop and apply a combined remote-sensing and flood-modelling approach to simulate the extent of pluvial flooding for a range of extreme precipitation events for historical (1984) and present-day (2014) urban land cover and for two climate-change scenarios (i.e. representative concentration pathways, RCP 4.5 and RCP 8.5). Changes in urban land cover are estimated using Landsat satellite imagery for the period 1984–2014. We combine the remote-sensing analyses with regionally downscaled estimates of precipitation extremes of current and expected future climate to enable 2-D overland flow simulations and flood-hazard assessments. The individual and combined impacts of urban development and climate change are quantified by examining the variations in flooding between the different simulations along with the corresponding uncertainties. In addition, two different assumptions are examined with regards to the development of the capacity of the urban drainage system in response to urban development and climate change. In the stationary approach, the capacity resembles present-day design, while it is updated in the evolutionary approach to correspond to changes in imperviousness and precipitation intensities due to urban development and climate change respectively. For all four cities, we find an increase in flood exposure corresponding to an observed absolute growth in impervious surfaces of 7–12 % during the past 30 years of urban development. Similarly, we find that climate change increases exposure to pluvial flooding under both the RCP 4.5 and RCP 8.5 scenarios. The relative importance of urban development and climate change on flood exposure varies considerably between the cities. For Odense, the impact of urban development is comparable to that of climate change under an RCP 8.5 scenario (2081–2100), while for Vienna and Strasbourg it is comparable to the impacts of an RCP 4.5 scenario. For Nice, climate change dominates urban development as the primary driver of changes in exposure to flooding. The variation between geographical locations is caused by differences in soil infiltration properties, historical trends in urban development and the projected regional impacts of climate change on extreme precipitation. Developing the capacity of the urban drainage system in relation to urban development is found to be an effective adaptation measure as it fully compensates for the increase in run-off caused by additional sealed surfaces. On the other hand, updating the drainage system according to changes in precipitation intensities caused by climate change only marginally reduces flooding for the most extreme events.

This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system is ongoing. In a HARMONIE-AROME 3-D forecast experiment we have shown that the frequency of the call for the radiation parametrization and choice of the parametrization scheme makes a difference to the surface radiation fluxes and changes the spatial distribution of the vertically integrated cloud cover and precipitation.

Abstract The near-term progression of ocean acidification (OA) is projected to bring about sharp changes in the chemistry of coastal upwelling ecosystems. The distribution of OA exposure across these early-impact systems, however, is highly uncertain and limits our understanding of whether and how spatial management actions can be deployed to ameliorate future impacts. Through a novel coastal OA observing network, we have uncovered a remarkably persistent spatial mosaic in the penetration of acidified waters into ecologically-important nearshore habitats across 1,000 km of the California Current Large Marine Ecosystem. In the most severe exposure hotspots, suboptimal conditions for calcifying organisms encompassed up to 56% of the summer season, and were accompanied by some of the lowest and most variable pH environments known for the surface ocean. Persistent refuge areas were also found, highlighting new opportunities for local adaptation to address the global challenge of OA in productive coastal systems.

Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

Urban water infrastructure has very long planning horizons, and planning is thus very dependent on reliable estimates of the impacts of climate change. Many urban water systems are designed using time series with a high temporal resolution. To assess the impact of climate change on these systems, similarly high-resolution precipitation time series for future climate are necessary. Climate models cannot at their current resolutions provide these time series at the relevant scales. Known methods for stochastic downscaling of climate change to urban hydrological scales have known shortcomings in constructing realistic climate-changed precipitation time series at the sub-hourly scale. In the present study we present a deterministic methodology to perturb historical precipitation time series at the minute scale to reflect non-linear expectations to climate change. The methodology shows good skill in meeting the expectations to climate change in extremes at the event scale when evaluated at different timescales from the minute to the daily scale. The methodology also shows good skill with respect to representing expected changes of seasonal precipitation. The methodology is very robust against the actual magnitude of the expected changes as well as the direction of the changes (increase or decrease), even for situations where the extremes are increasing for seasons that in general should have a decreasing trend in precipitation. The methodology can provide planners with valuable time series representing future climate that can be used as input to urban hydrological models and give better estimates of climate change impacts on these systems.

The direct shortwave radiative effect of aerosols under clear-sky conditions in the Aire Limitee Adaptation dynamique Developpement InterNational – High Resolution Limited Area Model (ALADIN-HIRLAM) numerical weather prediction system was investigated using three shortwave radiation schemes in diagnostic single-column experiments: the Integrated Forecast System (IFS), acraneb2 and the hlradia radiation schemes. The multi-band IFS scheme was formerly used operationally by the European Centre for Medium Range Weather Forecasts (ECMWF) whereas hlradia and acraneb2 are broadband schemes. The former is a new version of the HIRLAM radiation scheme while acraneb2 is the radiation scheme in the ALARO-1 physics package. The aim was to evaluate the strengths and weaknesses of the numerical weather prediction (NWP) system regarding aerosols and to prepare it for use of real-time aerosol information. The experiments were run with particular focus on the August 2010 Russian wildfire case. Each of the three radiation schemes accurately (within ±4 % at midday) simulates the direct shortwave aerosol effect when observed aerosol optical properties are used. When the aerosols were excluded from the simulations, errors of more than +15 % in global shortwave irradiance were found at midday, with the error reduced to +10 % when standard climatological aerosols were used. An error of −11 % was seen at midday if only observed aerosol optical depths at 550 nm, and not observation-based spectral dependence of aerosol optical depth, single scattering albedos and asymmetry factors, were included in the simulations. This demonstrates the importance of using the correct aerosol optical properties. The dependency of the direct radiative effect of aerosols on relative humidity was tested and shown to be within ±6 % in this case. By modifying the assumptions about the shape of the IFS climatological vertical aerosol profile, the inherent uncertainties associated with assuming fixed vertical profiles were investigated. The shortwave heating rates in the boundary layer changed by up to a factor of 2 in response to the aerosol vertical distribution without changing the total aerosol optical depth. Finally, we tested the radiative transfer approximations used in the three radiation schemes for typical aerosol optical properties compared to the accurate DISORT model. These approximations are found to be accurate to within ±13 % even for large aerosol loads.

Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km × 60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resolutions of 25 and 8 km, respectively. Six different RCM simulation pairs are used to perturb the WG with climate change signals resulting in six very different perturbation schemes. All perturbed WGs result in more extreme precipitation at the sub-daily to multi-daily level and these extremes exhibit a much more realistic spatial pattern than what is observed in RCM precipitation output. The WG seems to correlate increased extreme intensities with an increased spatial extent of the extremes meaning that the climate-change-perturbed extremes have a larger spatial extent than those of the present climate. Overall, the WG produces robust results and is seen as a reliable procedure for downscaling RCM precipitation output for use in urban hydrology.

We develop a theory for light propagating in an atomic Bose-Einstein condensate in the presence of strong interactions. The resulting many-body correlations are shown to have profound effects on the optical properties of this interacting medium. For weak atom-light coupling, there is a well-defined quasiparticle, the polaron-polariton, supporting light propagation with spectral features differing significantly from the noninteracting case. The damping of the polaron-polariton depends nonmonotonically on the light-matter coupling strength, initially increasing and then decreasing. This gives rise to an interesting crossover between two quasiparticles: a bare polariton and a polaron-polariton, separated by a complex and lossy mixture of light and matter.

The extent and location of impervious surfaces within urban areas due to past and present city development strongly affects the amount and velocity of run-off during high-intensity rainfall and consequently influences the exposure of cities towards flooding. The frequency and intensity of extreme rainfall are expected to increase in many places due to climate change and thus further exacerbate the risk of pluvial flooding. This paper presents a combined hydrological-hydrodynamic modelling and remote sensing approach suitable for examining the susceptibility of European cities to pluvial flooding owing to recent changes in urban land cover, under present and future climatic conditions. Estimated changes in impervious urban surfaces based on Landsat satellite imagery covering the period 1984–2014 are combined with regionally downscaled estimates of current and expected future rainfall extremes to enable 2-D overland flow simulations and flood hazard assessments. The methodology is evaluated for the Danish city of Odense. Results suggest that the past 30 years of urban development alone has increased the city's exposure to pluvial flooding by 6% for 10-year rainfall up to 26% for 100-year rainfall. Corresponding estimates for RCP4.5 and RCP8.5 climate change scenarios (2071–2100) are in the order of 40 and 100%, indicating that land cover changes within cities can play a central role for the cities' exposure to flooding and conversely also for their adaptation to a changed climate.

Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics, such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the atmosphere, catchment and river system that leave their fingerprints on flood characteristics. (3) Natural climate variability leads to time-varying flood characteristics, and this variation may be partially quantifiable and predictable, with the perspective of dynamic, climate-informed flood risk management. (4) Efforts are needed to fully account for factors that contribute to changes in all three risk components (hazard, exposure, vulnerability) and to better understand the interactions between society and floods. (5) Given the global scale and societal importance, we call for the organization of an international multidisciplinary collaboration and data-sharing initiative to further understand the links between climate and flooding and to advance flood research.

When short-wave (SW) radiation fluxes modelled with a numerical weather prediction (NWP) model or climate model do not match observed SW fluxes it can be challenging to find the cause of the differences. Several elements in the model affect SW fluxes. This necessitates individual testing of each of the physical processes in the NWP model. Here we present a focused study of the SW radiation schemes in the HIRLAM (HIgh Resolution Limited Area Model) Aladin Regional Mesoscale Operational NWP In Europe (HARMONIE) model, which is the primary NWP model used and developed by several National Weather Services in Europe. Detailed calculations have been made with the DISORT model run in the libRadtran framework, which is a collection of state-of-the-art radiative transfer software and data sets. These are used to test the NWP radiation calculations. Both models are given the same atmospheric properties as input. We also perform a separate test of cloud liquid optical property parameterisations with Mie calculations. This leads us to introduce a new parameterisation for calculating these properties. In addition, we show that the results of a simpler radiation scheme, introduced into HARMONIE, compare well with those of the comprehensive default parameterisations. The methodology applied here may be used for testing radiation schemes in other NWP or climate models.

In recent years, there has been an increase in the number of climate studies addressing changes in extreme precipitation. A common step in these studies involves the assessment of the climate model performance. This is often measured by comparing climate model output with observational data. In the majority of such studies the characteristics and uncertainties of the observational data are neglected. This study addresses the influence of using different observational data sets to assess the climate model performance. Four different data sets covering Denmark using different gauge systems and comprising both networks of point measurements and gridded data sets are considered. Additionally, the influence of using different performance indices and metrics is addressed. A set of indices ranging from mean to extreme precipitation properties is calculated for all the data sets. For each of the observational data sets, the regional climate models (RCMs) are ranked according to their performance using two different metrics. These are based on the error in representing the indices and the spatial pattern. In comparison to the mean, extreme precipitation indices are highly dependent on the spatial resolution of the observations. The spatial pattern also shows differences between the observational data sets. These differences have a clear impact on the ranking of the climate models, which is highly dependent on the observational data set, the index and the metric used. The results highlight the need to be aware of the properties of observational data chosen in order to avoid overconfident and misleading conclusions with respect to climate model performance.

We compare the cost of a high temperature superconducting (SC) tape-based solenoid with a permanent magnet (PM) Halbach cylinder for magnetic refrigeration. Assuming a five liter active magnetic regenerator volume, the price of each type of magnet is determined as a function of aspect ratio of the regenerator and desired internal magnetic field. It is shown that to produce a 1 T internal field in the regenerator a permanent magnet of hundreds of kilograms is needed or an area of superconducting tape of tens of square meters. The cost of cooling the SC solenoid is shown to be a small fraction of the cost of the SC tape. Assuming a cost of the SC tape of 6000 $/m2 and a price of the permanent magnet of 100 $/kg, the superconducting solenoid is shown to be a factor of 0.3-3 times more expensive than the permanent magnet, for a desired field from 0.5-1.75 T and the geometrical aspect ratio of the regenerator. This factor decreases for increasing field strength, indicating that the superconducting solenoid could be suitable for high field, large cooling power applications.

We study the quantum dynamics of a single impurity following its sudden immersion into a Bose–Einstein condensate. The ensuing formation of the Bose polaron in this general setting can be seen as impurity decoherence driven by the condensate, which we describe within a master equation approach. We derive rigorous analytical results for this decoherence dynamics, and thereby reveal distinct stages of its evolution from a universal stretched exponential initial relaxation to the final approach to equilibrium. The associated polaron formation time exhibits a strong dependence on the impurity speed and is found to undergo a critical slowdown around the speed of sound of the condensate. This rich non-equilibrium behavior of quantum impurities is of direct relevance to recent cold atom experiments, in which Bose polarons are created by a sudden quench of the impurity-bath interaction.