The diurnal cycle of shallow cumulus clouds over land: A single-column model intercomparison study

An intercomparison study for single-column models (SCMs) of the diurnal cycle of shallow cumulus convection is reported. The case, based on measurements at the Atmospheric Radiation Measurement program Southern Great Plains site on 21 June 1997, has been used in a large-eddy simulation intercomparison study before. Results of the SCMs reveal the following general deficiencies: too large values of cloud cover and Cloud liquid water, unrealistic thermodynamic profiles, and high amounts of numerical noise. Results are also strongly dependent on vertical resolution.These results are analysed in terms of the behaviour of the different parametrization schemes involved: the convection scheme, the turbulence scheme, and the cloud scheme. In general the behaviour of the SCMs can be grouped in two different classes: one class with too strong mixing by the turbulence scheme, the other class with too strong activity by the convection scheme. The coupling between (subcloud) turbulence and the convection scheme plays a crucial role. Finally, (in part) motivated by these results several models have been successfully updated with new parametrization schemes and/or their present schemes have been successfully modifie

Soil control on runoff response to climate change in regional climate model simulations

Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections

Relation of Iron Status to Prognosis After Acute Coronary Syndrome

Iron deficiency has been extensively researched and is associated with adverse outcomes in heart failure. However, to our knowledge, the temporal evolution of iron status has not been previously investigated in patients with acute coronary syndrome (ACS). Therefore, we aimed to explore the temporal pattern of repeatedly measured iron, ferritin, transferrin, and transferrin saturation (TSAT) in relation to prognosis post-ACS. BIOMArCS (BIOMarker study to identify the Acute risk of a Coronary Syndrome) is a prospective, multicenter, observational cohort study conducted in The Netherlands between 2008 and 2015. A total of 844 patients with post-ACS were enrolled and underwent high-frequency (median 17) blood sampling during 1 year follow-up. Biomarkers of iron status were measured batchwise in a central laboratory. We analyzed 3 patient subsets, including the case-cohort (n = 187). The primary endpoint (PE) was a composite of cardiovascular mortality and repeat nonfatal ACS, including unstable angina pectoris requiring revascularization. The association between iron status and the PE was analyzed using multivariable joint models. Mean age was 63 years; 78% were men, and >50% had iron deficiency at first sample in the case-cohort. After adjustment for a broad range of clinical variables, 1 SD decrease in log-iron was associated with a 2.2-fold greater risk of the PE (hazard ratio 2.19, 95% confidence interval 1.34 to 3.54, p = 0.002). Similarly, 1 SD decrease in log-TSAT was associated with a 78% increased risk of the PE (hazard ratio 1.78, 95% confidence interval 1.17 to 2.65, p = 0.006). Ferritin and transferrin were not associated with the PE. Repeated measurements of iron and TSAT predict risk of adverse outcomes in patients with post-ACS during 1 year follow-up. Trial Registration: The Netherlands Trial Register. Unique identifiers: NTR1698 and NTR1106. Registered at https://www.trialregister.nl/trial/1614 and https://www.trialregister.nl/trial/1073

Temporal Evolution of Serum Concentrations of High-Sensitivity Cardiac Troponin During 1 Year After Acute Coronary Syndrome Admission

BACKGROUND: Detailed insights in temporal evolution of high-sensitivity cardiac troponin following acute coronary syndrome (ACS) are currently missing. We aimed to describe and compare the post-ACS kinetics of high-sensitivity cardiac troponin I (hs-cTnI) and high-sensitivity cardiac troponin T (hs-cTnT), and to determine their intra- and interindividual variation in clinically stable patients. METHODS AND RESULTS: We determined hs-cTnI (Abbott) and hs-cTnT (Roche) in 1507 repeated blood samples, derived from 191 patients with ACS (median, 8/patient) who remained free from adverse cardiac events during 1-year follow-up. Post-ACS kinetics were studied by linear mixed-effect models. Using the samples collected in the 6- to 12-month post-ACS time frame, patients were then considered to have chronic coronary syndrome. We determined (differences between) the average hs-cTnI and average hs-cTnT concentration, and the intra- and interindividual variation for both biomarkers. Compared with hs-cTnT, hs-cTnI peaked higher (median 3506 ng/L versus 494 ng/L; P<0.001) and was quicker below the biomarker-specific upper reference limit (16 versus 19 days; P<0.001). In the post–6-month samples, hs-cTnI and hs-cTnT showed modest correlation (rspearman=0.60), whereas the average hs-cTnT concentration was 5 times more likely to be above the upper reference limit than hs-cTnI. The intraindividual variations of hs-cTnI and hs-cTnT were 14.0% and 18.1%, while the interindividual variations were 94.1% and 75.9%. CONCLUSIONS: Hs-cTnI peaked higher after ACS and was quicker below the upper reference limit. In the post–6-month samples, hs-cTnI and hs-cTnT were clearly not interchangeable, and average hs-cTnT concentrations were much more often above the upper reference limit than hs-cTnI. For both markers, the within-patient variation fell largely below beween-patient variation. REGISTRATION: URL: https://www.trialregister.nl; unique identifiers: NTR1698 and NTR1106

Intensification of summer precipitation with shorter time-scales in Europe

While daily extreme precipitation intensities increase with global warming on average at approximately the same rate as the availability of water vapor (~7%/°C), a debated topic is whether sub-daily extremes increase more. Modelling at convection-permitting scales has been deemed necessary to reproduce extreme summer precipitation at local scale. Here we analyze multi-model ensembles and apply a 3 km horizontal resolution model over four regions across Europe (S. Norway, Denmark, Benelux and Albania) and find very good agreement with observed daily and hourly summer precipitation extremes. Projections show that daily extreme precipitation intensifies compared to the mean in all regions and across a wide range of models and resolutions. Hourly and 10 min extremes intensify at a higher rate in nearly all regions. Unlike most recent studies, we do not find sub-daily precipitation extremes increasing much more than 7%/°C, even for sub-hourly extremes, but this may be due to robust summer drying over large parts of Europe. However, the absolute strongest local daily precipitation event in a 20 year period will increase by 10%–20%/°C. At the same time, model projections strongly indicate that summer drying will be more pronounced for extremely dry years

Refinement and application of a regional atmospheric model for climate scenario calculations of Western Europe

Het KNMI regionaal klimaat model RACMO wordt in toenemende mate gebruikt bij de detaillering van Klimaatscenario’s. Voorbeelden zijn de frequentie en intensiteit van hittegolven en de veranderingen daarin. Of te verwachten wijzigingen in het optreden van lokale neerslagextremen. In dit project zijn een aantal componenten van RACMO verder ontwikkeld. De bodemhydrologie van het model is verder verfijnd door ruimtelijke heterogeniteit in te voeren voor een aantal bodemparameters, zoals bodemtype en worteldiepte. Deze aanpassing resulteert in meer uitgesproken ruimtelijke structuren op regionale schaal

Temporal Evolution of Serum Concentrations of High-Sensitivity Cardiac Troponin During 1 Year After Acute Coronary Syndrome Admission

Background Detailed insights in temporal evolution of high-sensitivity cardiac troponin following acute coronary syndrome (ACS) are currently missing. We aimed to describe and compare the post-ACS kinetics of high-sensitivity cardiac troponin I (hs-cTnI) and high-sensitivity cardiac troponin T (hs-cTnT), and to determine their intra- and interindividual variation in clinically stable patients. Methods and Results We determined hs-cTnI (Abbott) and hs-cTnT (Roche) in 1507 repeated blood samples, derived from 191 patients with ACS (median, 8/patient) who remained free from adverse cardiac events during 1-year follow-up. Post-ACS kinetics were studied by linear mixed-effect models. Using the samples collected in the 6- to 12-month post-ACS time frame, patients were then considered to have chronic coronary syndrome. We determined (differences between) the average hs-cTnI and average hs-cTnT concentration, and the intra- and interindividual variation for both biomarkers. Compared with hs-cTnT, hs-cTnI peaked higher (median 3506 ng/L versus 494 ng/L; P<0.001) and was quicker below the biomarker-specific upper reference limit (16 versus 19 days; P<0.001). In the post-6-month samples, hs-cTnI and hs-cTnT showed modest correlation (rspearman

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes