Examination of the aerosol indirect effect under contrasting environments during the ACE-2 experiment

International audienceThe Active Tracer High-resolution Atmospheric Model (ATHAM) has been adopted to examine the aerosol indirect effect in contrasting clean and polluted cloudy boundary layers during the Second Aerosol Characterization Experiment (ACE-2). Model results are in good agreement with available in-situ observations, which provides confidence in the results of ATHAM. Sensitivity tests have been conducted to examine the response of the cloud fraction (CF), cloud liquid water path (LWP), and cloud optical depth (COD) to changes in aerosols in the clean and polluted cases. It is shown for two cases that CF and LWP would decrease or remain nearly constant with an increase in aerosols, a result which shows that the second aerosol indirect effect is positive or negligibly small in these cases. Further investigation indicates that the background meteorological conditions play a critical role in the response of CF and LWP to aerosols. When large-scale subsidence is weak as in the clean case, the dry overlying air above the cloud is more efficiently entrained into the cloud, and in so doing, removes cloud water more efficiently, and results in lower CF and LWP when aerosol burden increases. However, when the large-scale subsidence is strong as in the polluted case, the growth of the cloud top is suppressed and the entrainment drying makes no significant difference when aerosol burden increases. Therefore, the CF and LWP remain nearly constant. In both the clean and polluted cases, the COD tends to increase with aerosols, and the total aerosol indirect effect (AIE) is negative even when the CF and LWP decrease with an increase in aerosols. Therefore, the first AIE dominates the response of the cloud to aerosols

libcloudph++ 2.0: aqueous-phase chemistry extension of the particle-based cloud microphysics scheme

This paper introduces a new scheme available in the library of algorithms for representing cloud microphysics in numerical models named libcloudph++. The scheme extends the particle-based microphysics scheme with a Monte Carlo coalescence available in libcloudph++ to the aqueous-phase chemical processes occurring within cloud droplets. The representation of chemical processes focuses on the aqueous-phase oxidation of the dissolved SO2 by O3 and H2O2. The particle-based microphysics and chemistry scheme allows for tracking of the changes in the cloud condensation nuclei (CCN) distribution caused by both collisions between cloud droplets and aqueous-phase oxidation.The scheme is implemented in C++ and equipped with bindings to Python. The scheme can be used on either a CPU or a GPU, and is distributed under the GPLv3 license. Here, the particle-based microphysics and chemistry scheme is tested in a simple 0-dimensional adiabatic parcel model and then used in a 2-dimensional prescribed flow framework. The results are discussed with a focus on changes to the CCN sizes and comparison with other model simulations discussed in the literature.</p

Adaptive method of lines for multi-component aerosol condensational growth and CCN activation

The process of formation of cloud droplets on an ensemble of aerosol particles is modelled by numerous investigators using the method of lines (MOL). The method involves discretisation of the aerosol size spectrum into bins whose positions evolve with time. One of the drawbacks of the method is its poor representation of the aerosol spectrum shape in the region between the unactivated aerosol mode and the activated droplet mode. An adaptive grid refinement procedure is introduced. The procedure splits any overly wide bins into several narrower ones during integration. The number of new bins added is a function of particle concentration in the bin being split. Application of the grid refinement procedure results in suppression of the sensitivity of the computed cloud droplet spectrum characteristics such as droplet number concentration or effective radius to the initial grid choice. A model of droplet formation on multi-component aerosol is formulated for the purpose of the study. Model formulation includes explicit treatment of the droplet temperature evolution. Several examples of the model set-up are used to demonstrate model capabilities. Model results are compared to those without adaptivity. A C++ implementation of the model is available as an electronic supplement of the paper

Marine stratocumulus aerosol-cloud relationships in the MASE-II experiment: Precipitation susceptibility in eastern Pacific marine stratocumulus

Observational data on aerosol-cloud-drizzle relationships in marine stratocumulus are presented from the second Marine Stratus/Stratocumulus Experiment (MASE-II) carried out in July 2007 over the eastern Pacific near Monterey, California. Observations, carried out in regions of essentially uniform meteorology with localized aerosol enhancements due to ship exhaust (“ship tracks”), demonstrate, in accord with those from numerous other field campaigns, that increased cloud drop number concentration Nc and decreased cloud top effective radius r_e are associated with increased subcloud aerosol concentration. Modulation of drizzle by variations in aerosol levels is levels is clearly evident. Variations of cloud base drizzle rate R_(cb) are found to be consistent with the proportionality, R_(cb) / H^3/N_c, where H is cloud depth. Simultaneous aircraft and A-Train satellite observations are used to quantify the precipitation susceptibility of clouds to aerosol perturbations in the eastern Pacific region

Galleria mellonella as a host model to study Candida glabrata virulence and antifungal efficacy

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this record.This work was supported in part by the Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377/Z/11/

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth\u27s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods

Measurement of event-by-event transverse momentum and multiplicity fluctuations using strongly intensive measures Δ[PT,N]\Delta[P_T, N] and Σ[PT,N]\Sigma[P_T, N] in nucleus-nucleus collisions at the CERN Super Proton Synchrotron

Results from the NA49 experiment at the CERN SPS are presented on event-by-event transverse momentum and multiplicity fluctuations of charged particles, produced at forward rapidities in central Pb+Pb interactions at beam momenta 20$A$, 30$A$, 40$A$, 80$A$, and 158$A$ GeV/c, as well as in systems of different size ($p+p$, C+C, Si+Si, and Pb+Pb) at 158$A$ GeV/c. This publication extends the previous NA49 measurements of the strongly intensive measure $\Phi_{p_T}$ by a study of the recently proposed strongly intensive measures of fluctuations $\Delta[P_T, N]$ and $\Sigma[P_T, N]$. In the explored kinematic region transverse momentum and multiplicity fluctuations show no significant energy dependence in the SPS energy range. However, a remarkable system size dependence is observed for both $\Delta[P_T, N]$ and $\Sigma[P_T, N]$, with the largest values measured in peripheral Pb+Pb interactions. The results are compared with NA61/SHINE measurements in $p+p$ collisions, as well as with predictions of the UrQMD and EPOS models.Comment: 12 pages, 14 figures, to be submitted to PR

Antideuteron and deuteron production in mid-central Pb+Pb collisions at 158AA GeV

Production of deuterons and antideuterons was studied by the NA49 experiment in the 23.5% most central Pb+Pb collisions at the top SPS energy of $\sqrt{s_{NN}}$=17.3 GeV. Invariant yields for $\bar{d}$ and $d$ were measured as a function of centrality in the center-of-mass rapidity range $-1.2<y<-0.6$. Results for $\bar{d}(d)$ together with previously published $\bar{p}(p)$ measurements are discussed in the context of the coalescence model. The coalescence parameters $B_2$ were deduced as a function of transverse momentum $p_t$ and collision centrality.Comment: 9 figure

Bisphenol A-glycidyl methacrylate induces a broad spectrum of DNA damage in human lymphocytes

Bisphenol A-glycidyl methacrylate (BisGMA) is monomer of dental filling composites, which can be released from these materials and cause adverse biologic effects in human cells. In the present work, we investigated genotoxic effect of BisGMA on human lymphocytes and human acute lymphoblastic leukemia cell line (CCRF-CEM) cells. Our results indicate that BisGMA is genotoxic for human lymphocytes. The compound induced DNA damage evaluated by the alkaline, neutral, and pH 12.1 version of the comet assay. This damage included oxidative modifications of the DNA bases, as checked by DNA repair enzymes EndoIII and Fpg, alkali-labile sites and DNA double-strand breaks. BisGMA induced DNA-strand breaks in the isolated plasmid. Lymphocytes incubated with BisGMA at 1 mM were able to remove about 50% of DNA damage during 120-min repair incubation. The monomer at 1 mM evoked a delay of the cell cycle in the S phase in CCRF-CEM cells. The experiment with spin trap—DMPO demonstrated that BisGMA induced reactive oxygen species, which were able to damage DNA. BisGMA is able to induce a broad spectrum of DNA damage including severe DNA double-strand breaks, which can be responsible for a delay of the cell cycle in the S phase