Quantile forecast discrimination ability and value

While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are introduced here, based on quantile forecasts being the base product for the continuous case (hence in a nonparametric framework). The relative user characteristic (RUC) curve and the quantile value plot allow analysing the performance of a forecast for a specific user in a decision-making framework. The RUC curve is designed as a user-based discrimination tool and the quantile value plot translates forecast discrimination ability in terms of economic value. The relationship between the overall value of a quantile forecast and the respective quantile skill score is also discussed. The application of these new verification approaches and tools is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service

Classical skyrmions in SU(N)/SO(N) cosets

We construct the skyrmion solutions appearing in the coset spaces SU(N)/SO(N) for N > 2 and compute their classical mass. For N = 3, the third homotopy group pi_3(SU(3)/SO(3)) = Z_4 implies the existence of two distinct solutions: the skyrmion of winding number two has spherical symmetry and is found to be the lightest non-trivial field configuration; the skyrmion and antiskyrmion of winding number plus and minus one are slightly heavier and of toroidal shape. For N >= 4, there is only one skyrmion since the third homotopy group is Z_2. It is found to have spherical symmetry and is significantly lighter than the N = 3 solutions.Comment: 14 pages, 3 figures; v2: discussion improve

How to create an operational multi-model of seasonal forecasts?

Seasonal forecasts of variables like near-surface temperature or precipitation are becoming increasingly important for a wide range of stakeholders. Due to the many possibilities of recalibrating, combining, and verifying ensemble forecasts, there are ambiguities of which methods are most suitable. To address this we compare approaches how to process and verify multi-model seasonal forecasts based on a scientific assessment performed within the framework of the EU Copernicus Climate Change Service (C3S) Quality Assurance for Multi-model Seasonal Forecast Products (QA4Seas) contract C3S 51 lot 3. Our results underpin the importance of processing raw ensemble forecasts differently depending on the final forecast product needed. While ensemble forecasts benefit a lot from bias correction using climate conserving recalibration, this is not the case for the intrinsically bias adjusted multi-category probability forecasts. The same applies for multi-model combination. In this paper, we apply simple, but effective, approaches for multi-model combination of both forecast formats. Further, based on existing literature we recommend to use proper scoring rules like a sample version of the continuous ranked probability score and the ranked probability score for the verification of ensemble forecasts and multi-category probability forecasts, respectively. For a detailed global visualization of calibration as well as bias and dispersion errors, using the Chi-square decomposition of rank histograms proved to be appropriate for the analysis performed within QA4Seas.The research leading to these results is part of the Copernicus Climate Change Service (C3S) (Framework Agreement number C3S_51_Lot3_BSC), a program being implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. Francisco Doblas-Reyes acknowledges the support by the H2020 EUCP project (GA 776613) and the MINECO-funded CLINSA project (CGL2017-85791-R)

Global Analysis of Arabidopsis/Downy Mildew Interactions Reveals Prevalence of Incomplete Resistance and Rapid Evolution of Pathogen Recognition

Interactions between Arabidopsis thaliana and its native obligate oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) represent a model system to study evolution of natural variation in a host/pathogen interaction. Both Arabidopsis and Hpa genomes are sequenced and collections of different sub-species are available. We analyzed ∼400 interactions between different Arabidopsis accessions and five strains of Hpa. We examined the pathogen's overall ability to reproduce on a given host, and performed detailed cytological staining to assay for pathogen growth and hypersensitive cell death response in the host. We demonstrate that intermediate levels of resistance are prevalent among Arabidopsis populations and correlate strongly with host developmental stage. In addition to looking at plant responses to challenge by whole pathogen inoculations, we investigated the Arabidopsis resistance attributed to recognition of the individual Hpa effectors, ATR1 and ATR13. Our results suggest that recognition of these effectors is evolutionarily dynamic and does not form a single clade in overall Arabidopsis phylogeny for either effector. Furthermore, we show that the ultimate outcome of the interactions can be modified by the pathogen, despite a defined gene-for-gene resistance in the host. These data indicate that the outcome of disease and disease resistance depends on genome-for-genome interactions between the host and its pathogen, rather than single gene pairs as thought previously

The Spin Structure of the Nucleon

We present an overview of recent experimental and theoretical advances in our understanding of the spin structure of protons and neutrons.Comment: 84 pages, 29 figure

Development of surface plasmon resonance-based sensor for detection of silver nanoparticles in food and the environment

Silver nanoparticles are recognized as effective antimicrobial agents and have been implemented in various consumer products including washing machines, refrigerators, clothing, medical devices, and food packaging. Alongside the silver nanoparticles benefits, their novel properties have raised concerns about possible adverse effects on biological systems. To protect consumer’s health and the environment, efficient monitoring of silver nanoparticles needs to be established. Here, we present the development of human metallothionein (MT) based surface plasmon resonance (SPR) sensor for rapid detection of nanosilver. Incorporation of human metallothionein 1A to the sensor surface enables screening for potentially biologically active silver nanoparticles at parts per billion sensitivity. Other protein ligands were also tested for binding capacity of the nanosilver and were found to be inferior to the metallothionein. The biosensor has been characterized in terms of selectivity and sensitivity towards different types of silver nanoparticles and applied in measurements of real-life samples—such as fresh vegetables and river water. Our findings suggest that human MT1-based SPR sensor has the potential to be utilized as a routine screening method for silver nanoparticles, that can provide rapid and automated analysis dedicated to environmental and food safety monitoring

Bias adjustment and ensemble recalibration methods for seasonal forecasting: a comprehensive intercomparison using the C3S dataset

This work presents a comprehensive intercomparison of diferent alternatives for the calibration of seasonal forecasts, ranging from simple bias adjustment (BA)-e.g. quantile mapping-to more sophisticated ensemble recalibration (RC) methods- e.g. non-homogeneous Gaussian regression, which build on the temporal correspondence between the climate model and the corresponding observations to generate reliable predictions. To be as critical as possible, we validate the raw model and the calibrated forecasts in terms of a number of metrics which take into account diferent aspects of forecast quality (association, accuracy, discrimination and reliability). We focus on one-month lead forecasts of precipitation and temperature from four state-of-the-art seasonal forecasting systems, three of them included in the Copernicus Climate Change Service dataset (ECMWF-SEAS5, UK Met Ofce-GloSea5 and Météo France-System5) for boreal winter and summer over two illustrative regions with diferent skill characteristics (Europe and Southeast Asia). Our results indicate that both BA and RC methods efectively correct the large raw model biases, which is of paramount importance for users, particularly when directly using the climate model outputs to run impact models, or when computing climate indices depending on absolute values/thresholds. However, except for particular regions and/or seasons (typically with high skill), there is only marginal added value-with respect to the raw model outputs-beyond this bias removal. For those cases, RC methods can outperform BA ones, mostly due to an improvement in reliability. Finally, we also show that whereas an increase in the number of members only modestly afects the results obtained from calibration, longer hindcast periods lead to improved forecast quality, particularly for RC methods.This work has been funded by the C3S activity on Evaluation and Quality Control for seasonal forecasts. JMG was partially supported by the project MULTI-SDM (CGL2015-66583-R, MINECO/FEDER). FJDR was partially funded by the H2020 EUCP project (GA 776613)

Interactions between the night time valley-wind system and a developing cold-air pool

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Boundary-Layer Meteorology following peer review. The version of record [Arduini, G., Staquet, C & Chemel, C., ‘Interactions between the night time valley-wind system and a developing cold-air pool’, Boundary-Layer Meteorol (2016) 161:1 (49-72), first published online June 2, 2016, is available at Springer online at doi: 10.1007/s10546-016-0155-8The Weather Research and Forecast (WRF) numerical model is used to characterize the influence of a thermally-driven down-valley flow on a developing cold-air pool in an idealized alpine valley decoupled from the atmosphere above. Results for a three-dimensional (3D) valley, which allows for the formation of a down-valley flow, and for a two-dimensional (2D) valley, where the formation of a down-valley flow is inhibited, are analyzed and compared. A key result is that advection leads to a net cooling in the 2D valley and to a warming in the 3D valley, once the down-valley flow is fully developed. This difference stems from the suppression of the slope-flow induced upward motions over the valley centre in the 3D valley. As a result, the downslope flows develop a cross-valley circulation within the cold-air pool, the growth of the cold-air pool is reduced and the valley atmosphere is generally warmer than in the 2D valley. A quasi-steady state is reached for which the divergence of the down-valley flow along the valley is balanced by the convergence of the downslope flows at the top of the cold-air pool, with no net contribution of subsiding motions far from the slope layer. More precisely, the inflow of air at the top of the cold-air pool is found to be driven by an interplay between the return flow from the plain region and subsidence over the plateaux. Finally, the mechanisms that control the structure of the cold-air pool and its evolution are found to be independent of the valley length as soon as the quasi-steady state is reached and the down-valley flow is fully developed.Peer reviewedFinal Accepted Versio

Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed

Seropositivity and Risk Factors Associated with Toxoplasma gondii Infection in Wild Birds from Spain

Toxoplasma gondii is a zoonotic intracellular protozoan parasite of worldwide distribution that infects many species of warm-blooded animals, including birds. To date, there is scant information about the seropositivity of T. gondii and the risk factors associated with T. gondii infection in wild bird populations. In the present study, T. gondii infection was evaluated on sera obtained from 1079 wild birds belonging to 56 species (including Falconiformes (n = 610), Strigiformes (n = 260), Ciconiiformes (n = 156), Gruiformes (n = 21), and other orders (n = 32), from different areas of Spain. Antibodies to T. gondii (modified agglutination test, MAT titer ≥1∶25) were found in 282 (26.1%, IC95%:23.5–28.7) of the 1079 birds. This study constitute the first extensive survey in wild birds species in Spain and reports for the first time T. gondii antibodies in the griffon vulture (Gyps fulvus), short-toed snake-eagle (Circaetus gallicus), Bonelli's eagle (Aquila fasciata), golden eagle (Aquila chrysaetos), bearded vulture (Gypaetus barbatus), osprey (Pandion haliaetus), Montagu's harrier (Circus pygargus), Western marsh-harrier (Circus aeruginosus), peregrine falcon (Falco peregrinus), long-eared owl (Asio otus), common scops owl (Otus scops), Eurasian spoonbill (Platalea leucorodia), white stork (Ciconia ciconia), grey heron (Ardea cinerea), common moorhen (Gallinula chloropus); in the International Union for Conservation of Nature (IUCN) “vulnerable” Spanish imperial eagle (Aquila adalberti), lesser kestrel (Falco naumanni) and great bustard (Otis tarda); and in the IUCN “near threatened” red kite (Milvus milvus). The highest seropositivity by species was observed in the Eurasian eagle owl (Bubo bubo) (68.1%, 98 of 144). The main risk factors associated with T. gondii seropositivity in wild birds were age and diet, with the highest exposure in older animals and in carnivorous wild birds. The results showed that T. gondii infection is widespread and can be at a high level in many wild birds in Spain, most likely related to their feeding behaviour