Assessing adaptive mesh refinement (AMR) in a forced shallow-water model with moisture

Two forced shallow-water flow scenarios are explored in a 2D fourth-order finite-volume dynamical core with adaptive mesh refinement (AMR) to investigate AMR’s ability to track and resolve complex evolving features. Traditional shallow-water test cases are mainly characterized by large-scale smooth flows that do not effectively test the multiscale abilities of variable-resolution and AMR models to resolve sharp gradients and small-scale flow filaments. Therefore, adding forcing mechanisms to the shallow-water system to model key atmospheric processes adds complexity and creates small-scale phenomena. These can serve as foci for dynamic grid refinement while remaining simple enough to study the numerical design of a model’s dynamical core. The first shallow-water flow scenario represents a strengthening, tropical cyclone–like, vortex that is driven by a Betts–Miller-like convection scheme. The second shallow-water test is built upon a barotropically unstable jet with an added Kessler-like warm rain scheme that leads to precipitating frontal zones. The key feature of both tests is that there is significant sensitivity to the model grid while converging (structurally) at high resolution. Both test cases are investigated for a series of uniform resolutions and a variety of AMR tagging criteria. The AMR simulations demonstrate that grid refinement can resolve local features without requiring global high-resolution meshes. However, the results are sensitive to the refinement criteria. Criteria that trigger refinement early in a simulation reproduce the uniform-resolution reference solutions most reliably. In contrast, AMR criteria that delay refinement for several days require careful tuning of the AMR thresholds to improve results compared with uniform-resolution simulations

Impact of plasma jet vacuum ultraviolet radiation on reactive oxygen species generation in bio-relevant liquids

Plasma medicine utilizes the combined interaction of plasma produced reactive components. These are reactive atoms, molecules, ions, metastable species, and radiation. Here, ultraviolet (UV, 100–400 nm) and, in particular, vacuum ultraviolet (VUV, 10–200 nm) radiation generated by an atmospheric pressure argon plasma jet were investigated regarding plasma emission, absorption in a humidified atmosphere and in solutions relevant for plasma medicine. The energy absorption was obtained for simple solutions like distilled water (dH2O) or ultrapure water and sodium chloride (NaCl) solution as well as for more complex ones, for example, Rosewell Park Memorial Institute (RPMI 1640) cell culture media. As moderate stable reactive oxygen species, hydrogen peroxide (H2O2) was studied. Highly reactive oxygen radicals, namely, superoxide anion (O2•−) and hydroxyl radicals (•OH), were investigated by the use of electron paramagnetic resonance spectroscopy. All species amounts were detected for three different treatment cases: Plasma jet generated VUV and UV radiation, plasma jet generated UV radiation without VUV part, and complete plasma jet including all reactive components additionally to VUV and UV radiation. It was found that a considerable amount of radicals are generated by the plasma generated photoemission. From the experiments, estimation on the low hazard potential of plasma generated VUV radiation is discussed

Rotated Versions of the Jablonowski Steady‐State and Baroclinic Wave Test Cases: A Dynamical Core Intercomparison

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95316/1/jame31.pd

Physics–Dynamics Coupling in weather, climate and Earth system models: Challenges and recent progress

This is the final version. Available from American Meteorological Society via the DOI in this record.Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.Natural Environment Research Council (NERC)National Science FoundationDepartment of Energy Office of Biological and Environmental ResearchPacific Northwest National Laboratory (PNNL)DOE Office of Scienc

Zinc loading in urea-formaldehyde nanocomposites increases nitrogen and zinc micronutrient fertilization efficiencies in poor sand substrate.

Agricultural output needs significant increases to feed the growing population. Fertilizers are essential for plant production systems, with nitrogen (N) being the most limiting nutrient for plant growth. It is commonly supplied to crops as urea. Still, due to volatilization, up to 50 % of the total N application is lost. Slow or controlled release fertilizers are being developed to reduce these losses. The co-application of zinc (Zn) as a micronutrient can increase N absorption. Thus, we hypothesize that the controlled delivery of both nutrients (N and Zn) in an integrated system can improve uptake efficiency. Here we demonstrate an optimized fertilizer nanocomposite based on urea:urea-formaldehyde matrix loaded with ZnSO4 or ZnO. This nanocomposite effectively stimulates maize development, with consequent adequate N uptake, in an extreme condition ? a very nutrient-poor sand substrate. Our results indicate that the Zn co-application is beneficial for plant development. However, there were advantages for ZnO due to its high Zn content. We discuss that the dispersion favors the Zn delivery as the nanoparticulated oxide in the matrix. Concerning maize development, we found that root morphology is altered in the presence of the fertilizer nanocomposite. Increased root length and surface area may improve soil nutrient uptake, potentially accompanied by increased root exudation of essential compounds for N release from the composite structure

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each syste