The accurate prediction of aerodynamic drag on satellites orbiting in the upper atmosphere is critical to the operational success of modern space technologies, such as satellite‐based communication ...or navigation systems, which have become increasingly popular in the last few years due to the deployment of constellations of satellites in low‐Earth orbit. As a result, physics‐based models of the ionosphere and thermosphere have emerged as a necessary tool for the prediction of atmospheric outputs under highly variable space weather conditions. This paper proposes a high‐fidelity approach for physics‐based space weather modeling based on the solution of the Navier–Stokes equations using a high‐order discontinuous Galerkin method, combined with a matrix‐free strategy suitable for high‐performance computing on GPU architectures. The approach consists of a thermospheric model that describes a chemically frozen neutral atmosphere in nonhydrostatic equilibrium driven by the external excitation of the Sun. A novel set of variables is considered to treat the low densities present in the upper atmosphere and to accommodate the wide range of scales present in the problem. At the same time, and unlike most existing approaches, radial and angular directions are treated in a nonsegregated approach. The study presents a set of numerical examples that demonstrate the accuracy of the approximation and validate the current approach against observational data along a satellite orbit, including estimates of established empirical and physics‐based models of the ionosphere‐thermosphere system. Finally, a one‐dimensional radial derivation of the physics‐based model is presented and utilized for conducting a parametric study of the main thermal quantities under various solar conditions.
During the past few decades Acinetobacter baumannii has evolved from being a commensal dweller of health-care facilities to constitute one of the most annoying pathogens responsible for hospitalary ...outbreaks and it is currently considered one of the most important nosocomial pathogens. In a prevalence study of infections in intensive care units conducted among 75 countries of the five continents, this microorganism was found to be the fifth most common pathogen. Two main features contribute to the success of A. baumannii: (i) A. baumannii exhibits an outstanding ability to accumulate a great variety of resistance mechanisms acquired by different mechanisms, either mutations or acquisition of genetic elements such as plasmids, integrons, transposons, or resistant islands, making this microorganism multi- or pan-drug-resistant and (ii) The ability to survive in the environment during prolonged periods of time which, combined with its innate resistance to desiccation and disinfectants, makes A. baumannii almost impossible to eradicate from the clinical setting. In addition, its ability to produce biofilm greatly contributes to both persistence and resistance. In this review, the pathogenesis of the infections caused by this microorganism as well as the molecular bases of antibacterial resistance and clinical aspects such as treatment and potential future therapeutic strategies are discussed in depth.
Smoke from wildfires or burning biomass directly affects air quality and weather through modulating cloud microphysics and radiation. A simple wildfire emission coupling of black carbon (BC) and ...organic carbon (OC) with microphysics was implemented using the Weather Research and Forecasting model's fire module. A set of large‐eddy simulations inspired by unique surface and upper atmospheric observations from the 2021 Santa Coloma de Queralt Fire (Spain) were conducted to investigate the influence of background conditions and interactions between atmospheric and fire processes such as fire smoke, ambient moisture, and latent heat release on the formation and evolution of pyroconvective clouds. While the microphysical impact of BC and OC emissions on the dynamics of fire behavior is minimal on short time scales (<6 hr), their presence increased the cloud water content and decreased the rain rates in our case study. In our case study, atmospheric moisture played an important role in the formation and development of pyroconvective clouds, which in turn enhanced the surface winds (8%) and fire spread rate (25%). The influence of fuel moisture on the pyroconvective cloud formation is smaller when compared with the atmospheric moisture content. A better representation of cloud processes can improve the mesoscale forecasts, which is important for better fire behavior modeling.
Plain Language Summary
Pyroconvective clouds are formed directly as a result of wildland fires. They are influential on fire behavior, hard to predict, and impose hazardous conditions on the first responders and people in the area. Various environmental factors, such as atmospheric moisture, fuel moisture, fire intensity, and smoke, impact the formation and evolution of these clouds. Smoke from wildfires or burning biomass affects air quality and weather directly. The impact of smoke on the weather is either through radiative effects or cloud formation. Cloud water condensation can occur on the smoke particles where new cloud drops form. These processes are not currently represented in WRF‐Fire, a model simulating weather and wildfire evolution and interactions. We have implemented a simple emission model to represent the effect of smoke on the clouds. We investigated the impact of atmospheric and fuel moisture, as well as the smoke, on the pyroconvective clouds. We rely on unique in situ measurements to design our simulations and interpret the results. The availability of atmospheric moisture is essential for the formation of pyroconvective cloud. When a pyroconvective cloud forms, it creates faster winds, which, in turn cause faster fire propagation.
Key Points
A simple coupling of black and organic carbon emissions from wildfires to cloud microphysics
Environmental atmospheric moisture has a more significant influence than surface moisture release on the pyroconvective cloud formation
In our case study, the formation of pyroconvective clouds increased the surface winds and fire spread rate by 8% and 25%, respectively
Abstract
Condensation in cumulus clouds plays a key role in structuring the mean, nonprecipitating trade wind boundary layer. Here, we summarize how this role also explains the spontaneous growth of ...mesoscale >
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(10) km fluctuations in clouds and moisture around the mean state in a minimal-physics, large-eddy simulation of the undisturbed period during BOMEX on a large
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(100) km domain. Small, spatial anomalies in condensation in cumulus clouds, which form on top of small moisture fluctuations, power circulations that transport moisture, but not heat, from dry to moist regions, and thus reinforce the condensation anomaly. We frame this positive feedback as a linear instability in mesoscale moisture fluctuations, whose time scale depends only on (i) a vertical velocity scale and (ii) the mean environment’s vertical structure. In our minimal-physics setting, we show both ingredients are provided by the shallow cumulus convection itself: it is intrinsically unstable to length scale growth. The upshot is that energy released by clouds at kilometer scales may play a more profound and direct role in shaping the mesoscale trade wind environment than is generally appreciated, motivating further research into the mechanism’s relevance.
Numerical weather prediction models have become widespread tools that are accessible to a variety of communities, ranging from academia and the national meteorological services to commercial weather ...providers, wind and solar energy industries, and air quality modelers. Mesoscale meteorological models that are used to refine relatively coarse global weather forecasts to finer atmospheric scales have become mainstream. The wide use of mesoscale meteorological models also generates new requirements in undergraduate education concerning the knowledge and application of these models. In this paper, we present teaching strategies, course outcomes, student activities, impacts, and reflections on the possible future direction of the graduate-level atmospheric modeling course using the Weather Research and Forecasting (WRF) Model at Wageningen University, the Netherlands. This information is based on 15 years of experience in teaching the course and the continuous implementation of new educational techniques to adapt to students’ needs and improve their chances in their academic careers and the atmospheric sciences job market.
This work presents a review of high-order hybridisable discontinuous Galerkin (HDG) methods in the context of compressible flows. Moreover, an original unified framework for the derivation of Riemann ...solvers in hybridised formulations is proposed. This framework includes, for the first time in an HDG context, the HLL and HLLEM Riemann solvers as well as the traditional Lax–Friedrichs and Roe solvers. HLL-type Riemann solvers demonstrate their superiority with respect to Roe in supersonic cases due to their positivity preserving properties. In addition, HLLEM specifically outstands in the approximation of boundary layers because of its shear preservation, which confers it an increased accuracy with respect to HLL and Lax–Friedrichs. A comprehensive set of relevant numerical benchmarks of viscous and inviscid compressible flows is presented. The test cases are used to evaluate the competitiveness of the resulting high-order HDG scheme with the aforementioned Riemann solvers and equipped with a shock treatment technique based on artificial viscosity.
Conventional microbiological procedures for the isolation of bacteria from biological fluids consist of culture on solid media and enrichment broth. However, these methods can delay the ...microbiological identification for up to 4 days. The aim of this study was to evaluate the analytical performance of Sysmex UF500i (Sysmex, Kobe, Japan) as a screening method for the detection of bacteria in different biological fluids in comparison with direct Gram staining and the conventional culture on solid media and enrichment broth.
A total of 479 biological fluid samples were included in the study (180 ascitic, 131 amniotic, 56 synovial, 40 cerebrospinal, 36 pleural, 24 peritoneal, 9 bile and 3 pericardial fluids). All samples were processed by conventional culture methods and analyzed by flow cytometry. Direct Gram staining was performed in 339 samples. The amount of growth on culture was recorded for positive samples.
Bacterial and white blood cell count by flow cytometry was significantly higher among culture positive samples and samples with a positive direct Gram stain compared to culture negative samples. Bacterial count directly correlated with the amount of growth on culture (Kruskall-Wallis H χ2(3) = 11.577, p = 0.009). The best specificity (95%) for bacterial count to predict culture positivity was achieved applying a cut-off value of 240 bacteria/μL.
Bacterial and white blood cell counts obtained with flow cytometry correlate with culture results in biological fluids. Bacterial count can be used as a complementary method along with the direct Gram stain to promptly detect positive samples and perform other diagnostic techniques in order to accelerate the bacterial detection and identification.
Complete diagnostic autopsies (CDA) remain the gold standard in the determination of cause of death (CoD). However, performing CDAs in developing countries is challenging due to limited facilities ...and human resources, and poor acceptability. We aimed to develop and test a simplified minimally invasive autopsy (MIA) procedure involving organ-directed sampling with microbiology and pathology analyses implementable by trained technicians in low- income settings.
A standardized scheme for the MIA has been developed and tested in a series of 30 autopsies performed at the Maputo Central Hospital, Mozambique. The procedure involves the collection of 20 mL of blood and cerebrospinal fluid (CSF) and puncture of liver, lungs, heart, spleen, kidneys, bone marrow and brain in all cases plus uterus in women of childbearing age, using biopsy needles.
The sampling success ranged from 67% for the kidney to 100% for blood, CSF, lung, liver and brain. The amount of tissue obtained in the procedure varied from less than 10 mm2 for the lung, spleen and kidney, to over 35 mm2 for the liver and brain. A CoD was identified in the histological and/or the microbiological analysis in 83% of the MIAs.
A simplified MIA technique allows obtaining adequate material from body fluids and major organs leading to accurate diagnoses. This procedure could improve the determination of CoD in developing countries.
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