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There is a growing research interest in understanding extreme weather in the context of anthropogenic climate change, posing a requirement for new tailored climate data products. Here we introduce the Climate of the 20th Century Plus Detection and Attribution project (C20C + D&A), an international collaboration generating a product specifically intended for diagnosing causes of changes in extreme weather and for understanding uncertainties in that diagnosis. The project runs multiple dynamical models of the atmosphere-land system under observed historical conditions as well as under naturalised versions of those observed conditions, with the latter representing how the climate system might have evolved in the absence of anthropogenic interference. Each model generates large ensembles of simulations with different initial conditions for each historical scenario, providing a large sample size for understanding interannual variability, long-term trends, and the anthropogenic role in rare types of weather. This paper describes the C20C + D&A project design, implementation, strengths, and limitations, and also discusses various activities such as this special issue of Weather and Climate Extremes dedicated to “First results of the C20C + Detection and Attribution project”.

Introduction Materials and Methods Results Conclusions The increase in the migration of dentists educated outside the EU/EEA calls for the sharing of information and evaluation of recognition processes within countries in the EU. In 2017, the Swedish National Board of Health and Welfare implemented the Proficiency test, a recognition process for dentists who have completed an education programme outside the EU/EEA. The Proficiency test consists of a theoretical and an integrated clinical skills examination, followed by a 6‐month clinical practice. The clinical skills examination is a two‐part examination that includes an OSCE and an operative test on a dental manikin. This paper presents data from proficiency tests between 2018 and 2022, and explores factors related to grade fail, that is, demographics, theoretical exam scores and language comprehension.In a cohort study, demographics and factors associated with grade fail were explored using test results from theoretical and clinical skills examinations (n = 181) from 2018 to 2022. Pearson correlation coefficient and linear regression analysis were used for studying correlations and associations between exam results. Univariable linear and logistic regression models were used for background variable associations with clinical skills exam outcomes.Higher age was a significant risk factor for failing the clinical skills examination and the OSCE. Higher scores in the theoretical exam reduced the odds of failing the OSCE but were not associated with results in the operative test or the overall results of the clinical skills examination. Regarding the OSCE there was a statistically significant difference within all professional qualifications explored between participants who passed and participants who failed the OSCE.Four years of data collection reveal that age and previous theoretical exam results influence the odds of failing the clinical examination. The study results also highlight the necessity of multiple assessment formats to assess clinical and communication skills of foreign‐trained dentists. [ABSTRACT FROM AUTHOR]

We examine the effect of the 20th and recent 21st century anthropogenic climate change on high temperature extremes as simulated by four global atmospheric general circulation models submitted to the Climate of the 20th Century Plus Detection and Attribution project. This coordinated experiment is based upon two large ensembles simulations for each participating model. The “world that was” simulations are externally forced as realistically as possible. The “world that might have been” is identical except that the influence of human forcing is removed but natural forcing agents and variations in ocean and sea ice are retained. We apply a stationary generalized extreme value analysis to the annual maxima of the three day average of the daily maximum surface air temperature, finding that long period return values have been increased by human activities between 1 and 3 °C over most land areas. Corresponding changes in the probability of achieving long period non-industrial return values in the industrialized world are also presented. We find that most regions experience increases in the frequency and intensity of extremely hot three day periods, but anthropogenic sulfate aerosol forcing changes locally can decrease these measures of heat waves in some models.

In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.

A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.

Late spring (April-May) is normally the end of the dry season in South China, but 2018 was an exception. An extreme drought condition developed over South China (22[degrees]-29[degrees]N, 105[degrees]-120[degrees]E; box [...]

Background: Bruxism is an umbrella term that encompass a multidimensional spectrum of masticatory muscle activities. Objective: The purpose of this study was to do a bibliometric analysis including citation performance in the research topic of bruxism, by using an innovative method including details of article title, author keyword, KeyWords Plus and abstracts. Methods: The data were retrieved 2022‐12‐19 from the Clarivate Analytics Web of Science Core Collection, and the online version of the Science Citation Index Expanded (SCI‐EXPANDED) for studies published 1992 to 2021. To evaluate research trends, the distribution of keywords in the article title and author‐selected keywords were used. Results: The search yielded 3233 documents in SCI‐EXPANDED, of which 2598 were of the document‐type 'articles' published in 676 journals. The analysis of the articles revealed that "bruxism/sleep bruxism," "electromyography," "temporomandibular disorders" and "masticatory muscles" are the most used keywords by the authors. Further, the most frequently cited study was published 9 years ago and handles the present definition of bruxism. Conclusion: The most productive authors and those with the highest performance have some common features; they have several national and international collaborations; and they have published articles about the definition, aetiology/pathophysiology and prevalence of bruxism, all senior researchers in the field of TMD. Hopefully, based on this study, researchers and clinicians will have information to be stimulated to outline future research projects on bruxism‐related aspects, and to initiate new international or multinational collaborations. [ABSTRACT FROM AUTHOR]

INTRODUCTION. Peru's rainy season falls in the first quarter of the year, often dubbed the 'landslide season,' with the direst downpours typically occurring in March (Lavado Casimiro et al. 2012). [...]