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Abstract Background Serum creatinine and symmetric dimethylarginine (SDMA) are used as surrogate markers of glomerular filtration rate (GFR) in clinical practice. Data pertaining to the correlations between GFR, SDMA, and serum creatinine in client‐owned dogs are limited. Objectives To describe the relationship between GFR, SDMA, and serum creatinine in a population of client‐owned dogs, and to compare clinical utility of SDMA to GFR estimation for detecting pre‐azotemic chronic kidney disease. Animals Medical records of 119 dogs that had GFR estimation performed via serum iohexol clearance between 2012 and 2017. Methods Prospective study using archived samples. GFR, SDMA, and serum creatinine results were reviewed and submitting practices contacted for outcome data. All dogs included in the study population were non‐azotemic. Correlations between GFR, SDMA, and serum creatinine were determined by regression analysis. Sensitivity, specificity, and positive and negative likelihood ratios of different cutoffs for SDMA and serum creatinine for detecting decreased GFR were calculated, using a 95% confidence interval. Results Serum creatinine and SDMA were moderately correlated with GFR (R2 = 0.52 and 0.27, respectively, P < .0001) and with each other (R2 = 0.33, P < .0001). SDMA >14 μg/dL was sensitive (90%) but nonspecific (50%) for detecting a ≥40% decrease in GFR. Optimal SDMA concentration cutoff for detecting a ≥40% GFR decrease was >18 μg/dL (sensitivity 90%, specificity 83%). Conclusions and Clinical Importance In non‐azotemic dogs being screened for decreased renal function, using a cutoff of >18 μg/dL rather than >14 μg/dL increases the specificity of SDMA, without compromising sensitivity.

Abstract The Northwest European shelf experienced unprecedented surface temperature anomalies in June 2023 (anomalies up to 5 °C locally, north of Ireland). Here, we show the shelf average underwent its longest recorded category II marine heatwave (16 days). With state-of-the-art observation and modelling capabilities, we show the marine heatwave developed quickly due to strong atmospheric forcing (high level of sunshine, weak winds, tropical air) and weak wave activity under anticyclonic weather regimes. Once formed, this shallow marine heatwave fed back on the weather: over the sea it reduced cloud cover and over land it contributed to breaking June mean temperature records and to enhanced convective rainfall through stronger, warmer and moister sea breezes. This marine heatwave was intensified by the last 20-year warming trend in sea surface temperatures. Such sea surface temperatures are projected to become commonplace by the middle of the century under a high greenhouse gas emission scenario.

The flooding in South Yorkshire in the United Kingdom (UK) in autumn 2019 saw one fatality, at least 500 properties flooded and 1 200 households evacuated. The worst of the flooding occurred after very high 24-h rainfall totals of up to 82 mm fell on already saturated ground. This followed very high 24-h rainfall totals in the region just two weeks earlier of up to just under 50 mm. In the light of anthropogenic climate change, it is expected that extreme rainfall events are set to become more intense as a result of increased global mean temperatures and the Clausius-Clapeyron relation. Here we investigate the change in risk of such extreme rainfall events in the UK in autumn using a new index R50mm_OND, representing the mean number of daily precipitation totals in excess of 50 mm in October–December each year. Using high resolution regional model datasets and observations we show that extreme rainfall totals for the UK are increasing exponentially as a result of anthropogenic climate change. Observations show that the frequency of extreme daily precipitation in the form of R50mm_OND has already increased by 60% (95% CI: 44–76) in the UK between the beginning of the 20th and 21st centuries. R50mm_OND is projected to increase even further between 2019 and 2080, by 85% (95% CI: 73–97) according to a Representative Concentration Pathway (RCP) 8.5 scenario of anthropogenic emissions. While higher resolution models (12 km spatial resolution) were able to capture the observed changes, lower resolution models were not. This underlines the importance of high-resolution models for modelling extreme precipitation seen in late autumn and early winter, not just for convective rainfall in the summer. A more specific analysis of the November 2019 event looked at the mean of the two highest daily precipitation totals in October–November in the South Yorkshire region. This found a long-term shift to higher daily rainfall totals for this mean with an increase in intensity of the top 10% of events, suggesting that the South Yorkshire region in autumn is more at risk of flooding in the future without effective adaptation measures.

Abstract The breaking of the United Kingdom's daily rainfall record in October 2020 made a striking addition to the list of recent heavy precipitation events in the country. Mounting evidence from attribution research suggests that such extremes become more frequent and intense in a warming climate. Although most studies consider extreme events in specific months or seasons, here we investigate for the first time how extremes of the wettest day of the year may be influenced by anthropogenic forcings. Data from large multimodel ensembles indicate that the moderate historical trend towards wetter conditions will emerge more strongly in coming decades, while a notable anthropogenic influence on the variability of the wettest day may be identified as early as the 1900s. Experiments with different forcings are employed to estimate the changing probability of extremes due to anthropogenic climate change in a risk‐based attribution framework. We introduce a new methodology of estimating probabilities of extremes in the present and future that calibrates data from long simulations of the preindustrial climate to the mean state and variability of the reference climatic period. The new approach utilises larger samples of rainfall data than alternative methods, which is a major advantage when analysing extremely rare events. The record rainfall of the wettest day in year 2020 is estimated to have become about 2.5 times more likely because of human influence, while its return time, currently about 100 years, will decrease to only about 30 years by 2100. Compared to a hypothetical natural climate, we estimate a 10‐fold increase in the chances of such extreme rainfall events in the United Kingdom by the end of this century, which underlines the need for effective adaptation planning.