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The role of vertical mesh spacing in the convergence of full-physics global atmospheric model solutions is examined for synoptic, mesoscale, and convective-scale horizontal resolutions. Using the MPAS-Atmosphere model, convergence is evaluated for three solution metrics: the horizontal kinetic energy spectrum, the Richardson number probability density function, and resolved flow features. All three metrics exhibit convergence in the free atmosphere for a 15-km horizontal mesh when the vertical grid spacing is less than or equal to 200 m. Nonconvergence is accompanied by noise, spurious structures, reduced levels of mesoscale kinetic energy, and reduced Richardson number peak frequencies. Coarser horizontal mesh solutions converge in a similar manner but contain much less noise than the 15-km solutions for coarse vertical resolution. For convective-scale resolution simulations with 3-km cell spacing on a variable-resolution mesh, solution convergence is almost attained with a vertical mesh spacing of 200 m. The boundary layer scheme is the dominant source of vertical filtering in the free atmosphere. Although the increased vertical mixing at coarser vertical mesh spacing depresses the kinetic energy spectra and Richardson number convergence, it does not produce sufficient dissipation to effectively halt scale collapse. These results confirm and extend the results from a number of previous studies, and further emphasize the sensitivity of the energetics to the vertical mixing formulations in the model.

Lakes affect local weather and climate. This influence should be taken into account in NWP models through parameterization. For the atmospheric simulation, global coverage of lake depth data is essential. To provide such data Global Lake Database (GLDB) has been created. GLDB contains information about lake location (latitude, longitude), water surface area, and lake mean and max depths. The mean depth is provided as a gridded data set.

In order to enlarge our understanding of biomass burning plume chemistry, the OH radical initiated oxidation of 3-penten-2-one (3P2), identified in biomass burning emissions, and 2-hydroxypropanal (2HPr) were investigated at 298 ± 3 K and 990 ± 15 mbar in two atmospheric simulation chambers using long-path FTIR spectroscopy. The rate coefficient of 3P2 + OH was determined to be (6.2 ± 1.0) × 10−11 cm3 molecule−1 s−1 and the molar first-generation yields for acetaldehyde, methyl glyoxal, 2HPr and the sum of PAN and CO2, used to determine the CH3C(O) radical yield, were 0.39 ± 0.07, 0.32 ± 0.08, 0.68 ± 0.27, and 0.56 ± 0.14, respectively, under conditions where the 3P2 derived peroxy radicals react solely with NO. The 2HPr + OH reaction was investigated using 3P2 + OH as a source of the α-hydroxyaldehyde adjusting the experimental conditions to shift the reaction system towards secondary oxidation processes. The rate coefficient was estimated to be (2.2 ± 0.6) × 10−11 cm3 molecule−1 s−1. Employing an Euler-Cauchy model to describe the temporal behaviour of the experiments, the further oxidation of 2HPr was shown to form methyl glyoxal, acetaldehyde and CO2 with estimated yields of 0.21 ± 0.05, 0.79 ± 0.05, and 0.79 ± 0.05, respectively.

We analysed the biogenic volatile organic compounds (BVOC) emissions from rapeseed leaves litter and their potential to create secondary organic aerosols (SOA) under three different conditions i.e., (i) in presence of UV light irradiation; (ii) in presence of ozone, and (iii) with both ozone and UV light. These experiments have been performed in a controlled atmospheric simulation chamber containing leaves litter samples, where BVOC and aerosol number concentrations have been measured for 6 days. Our results show that BVOC emission profiles were affected by UV light irradiation, which increased the summed BVOC emissions compared to the experiment with solely O3. Furthermore, the diversity of emitted VOCs from the rapeseed litter increased also in presence of UV light irradiation. SOA formation was observed when leaves litter were exposed to both UV light and O3, indicating a potentially large contribution to particle formation or growth at local scales. To our knowledge, this study investigates for the first time the effect of UV irradiation and O3 exposure on both VOC emissions and SOA formation for leaves litter samples. A detailed discussion about the processes behind the biological production of the most important VOC is proposed.

Correcting historical sea surface temperature improves the simulation of 19th- and 20th-century North Atlantic hurricane activity., Confidence in dynamical and statistical hurricane prediction is rooted in the skillful reproduction of hurricane frequency using sea surface temperature (SST) patterns, but an ensemble of high-resolution atmospheric simulation extending to the 1880s indicates model-data disagreements that exceed those expected from documented uncertainties. We apply recently developed corrections for biases in historical SSTs that lead to revisions in tropical to subtropical SST gradients by ±0.1°C. Revised atmospheric simulations have 20% adjustments in the decadal variations of hurricane frequency and become more consistent with observations. The improved simulation skill from revised SST estimates not only supports the utility of high-resolution atmospheric models for hurricane projections but also highlights the need for accurate estimates of past and future patterns of SST changes.

A promising approach to improve climate-model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data-driven. However, neural networks (NNs) often lead to instabilities and climate drift when coupled to an atmospheric model. Here we learn an NN parameterization from a high-resolution atmospheric simulation in an idealized domain by coarse graining the model equations and output. The NN parameterization has a structure that ensures physical constraints are respected, and it leads to stable simulations that replicate the climate of the high-resolution simulation with similar accuracy to a successful random-forest parameterization while needing far less memory. We find that the simulations are stable for a variety of NN architectures and horizontal resolutions, and that an NN with substantially reduced numerical precision could decrease computational costs without affecting the quality of simulations., 23 pages, 6 figures (2 figures in main file)

Experiments at a set of atmospherically relevant conditions were performed in the atmospheric simulation chamber SAPHIR, investigating the oxidation of isoprene by the nitrate radical (NO3). A comprehensive set of instruments detected trace gases, radicals, aerosol properties and hydroxyl (OH) and NO3 radical reactivity. The chemical conditions in the chamber were varied to change the fate of the peroxy radicals (RO2) formed after the reaction between NO3 and isoprene, and seed aerosol of varying composition was added to initiate gas/aerosol partitioning. This presentation discusses observed gas/aerosol partitioning of the major organic nitrate products and summarizes the observations of secondary organic aerosol yield.

Visualization is an important and ubiquitous tool in the daily work of atmospheric researchers and weather forecasters to analyse data from simulations and observations. Visualization research has made much progress in recent years, in particular with respect to techniques for ensemble data, interactivity, 3D depiction, and feature-detection. Transfer of new techniques into the atmospheric sciences, however, is slow.Met.3D (https://met3d.wavestoweather.de) is an open-source research software aiming at making novel interactive 3D and ensemble visualization techniques accessible to the atmospheric community. Since its first public release in 2015, Met.3D has been used in multiple visualization research projects targeted at atmospheric science applications, and also has evolved into a feature-rich visual analysis tool facilitating rapid exploration of atmospheric simulation data. The software is based on the concept of “building a bridge” between “traditional” 2D visual analysis techniques and interactive 3D techniques and allows users to analyse their data using combinations of 2D maps and cross-sections, meteorological diagrams and 3D techniques including direct volume rendering, isosurfaces and trajectories, all combined in an interactive 3D context.This PICO will provide an overview of the Met.3D project and highlight recent additions and improvements to the software. We will show several examples of how the combination of 2D and 3D visualization elements in an interactive context can be used to explore atmospheric simulation data, including the analysis of forecast errors, analysis of synoptic-scale features including jet-streams and fronts, and analysis of forecast uncertainty in ensemble forecasts.

This article demonstrates an approach for combining general tuning techniques with the POWER8 hardware architecture through optimizing three representative stencil benchmarks. Two typical real-world applications, with kernels similar to those of the winning programs of the Gordon Bell Prize 2016 and 2017, are employed to illustrate algorithm modifications and a combination of hardware-oriented tuning strategies with the application algorithms. This work fills the gap between hardware capability and software performance of the POWER8 processor, and provides useful guidance for optimizing stencil-based scientific applications on POWER systems.

Large-eddy-resolving simulations using the Collaborative Model for Multiscale Atmospheric Simulation (COMMAS), which contains microphysical charging and branched-lightning parameterizations, produce much more complex net charge structures than conventionally visualized from previous observations, simulations, and conceptual diagrams. Many processes contribute to the hydrometeor charge budget within a thunderstorm, including advection, hydrometeor differential sedimentation, subgrid turbulent mixing and diffusion, ion drift, microphysical separation, and the attachment of ion charge deposited by the lightning channel. The lightning deposition, sedimentation, and noninductive charging tendencies contribute the most overall charge at relatively large scales, while the advection tendency, from resolved turbulence, provides the most “texture” at small scales to the net charge density near the updraft region of the storm. The scale separation increases for stronger storm simulations. In aggregate, lightning deposition and sedimentation resemble the smoother distribution of the electric potential, while evidence suggests individual flashes could be responding to the fine texture in the net charge. The clear scale separation between the advection and other net charge tendencies suggest the charge advection is most capable of providing net charge texture; however, a clear-cut causality is not obtained from this study.

Rate coefficients for the gas-phase reactions of OH radicals with a series of fluorinated diketones have been determined for the first time at (298 ± 3) K and atmospheric pressure using the relative method and FTIR spectroscopy and GC-FID to monitor both reactants and references. The following values, in 10−11 cm3 molecule−1 s−1, were obtained for 1,1,1-trifluoro-2,4-pentanedione (TFP), 1,1,1-trifluoro-2,4-hexanedione (TFH) and 1,1,1-trifluoro-5-methyl-2,4-hexanedione (TFMH), respectively: k1(TFP + OH) = (1.3 ± 0.4), k2(TFH + OH) = (2.2 ± 0.8), k3(TFMH + OH) = (3.3 ± 1.0). The results are discussed with respect to the keto-enolic tautomerization specific for β-diketones. Based on the present results, the tropospheric lifetimes of TFP, TFH and TFMH upon degradation by OH radicals were calculated as 21, 13 and 8 h, respectively indicating that transport might play a role in the atmospheric fate of the studied compounds. Photochemical ozone creation potentials were estimated for TFP, TFH and TFMH to be: 23, 29 and 34, respectively.

Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

Theoretical, laboratory and chamber studies have shown fast regeneration of hydroxyl radical (OH) in the photochemistry of isoprene largely due to previously disregarded unimolecular reactions which were previously thought not to be important under atmospheric conditions. Based on early field measurements, nearly complete regeneration was hypothesized for a wide range of tropospheric conditions, including areas such as the rainforest where slow regeneration of OH radicals is expected due to low concentrations of nitric oxide (NO). In this work the OH regeneration in the isoprene oxidation is directly quantified for the first time through experiments covering a wide range of atmospheric conditions (i.e. NO between 0.15 and 2 ppbv and temperature between 25 and 41°C) in the atmospheric simulation chamber SAPHIR. These conditions cover remote areas partially influenced by anthropogenic NO emissions, giving a regeneration efficiency of OH close to one, and areas like the Amazonian rainforest with very low NO, resulting in a surprisingly high regeneration efficiency of 0.5, i.e. a factor of 2 to 3 higher than explainable in the absence of unimolecular reactions. The measured radical concentrations were compared to model calculations and the best agreement was observed when at least 50% of the total loss of isoprene peroxy radicals conformers (weighted by their abundance) occurs via isomerization reactions for NO lower than 0.2 parts per billion (ppbv). For these levels of NO, up to 50% of the OH radicals are regenerated from the products of the 1,6 α-hydroxy-hydrogen shift (1,6-H shift) of Z-δ-RO2 radicals through photolysis of an unsaturated hydroperoxy aldehyde (HPALD) and/or through the fast aldehyde hydrogen shift (rate constant ~10 s-1 at 300K) in di-hydroperoxy carbonyl peroxy radicals (di-HPCARP-RO2), depending on their relative yield. The agreement between all measured and modelled trace gases (hydroxyl, hydroperoxy and organic peroxy radicals, carbon monoxide and the sum of methyl vinyl ketone, methacrolein and hydroxyl hydroperoxides) is nearly independent on the adopted yield of HPALD and di-HPCARP-RO2 as both degrade relatively fast (< 1 h), forming OH radical and CO among other products. Taking into consideration this and earlier isoprene studies, considerable uncertainties remain on the oxygenated products distribution, which affect radical levels and organic aerosol downwind of unpolluted isoprene dominated regions.

Air quality is a major health and environmental issue worldwide. Similarly, the accuracy of wind resource assessment triggers significant economic and environmental repercussions. In order to study these two topics, it is necessary to accurately determine local wind fields using numerical models of micrometeorology. Such simulations are extremely sensitive to meteorological conditions at the domain borders. Up to present, the boundary conditions (BC) were estimated based on the results of larger scale simulations, which provide information that is not accurate enough, or even incomplete, for local scale purposes. As a matter of fact, the lack of knowledge about the BC represents a major source of error and uncertainty for micrometeorological studies.The potential sites for wind farm installation as well as built environments (urban areas or industrial sites) can be equipped with instruments measuring meteorological variables or pollutant concentration. The observations provided by these instruments represent a second source of information, insufficiently exploited for micrometeorological studies. Indeed, the in situ measurements are perturbed by the complex geometrical features on sites and might be difficult to exploit. In order to improve the exactitude and the accuracy of the BC, and consequently of the locale-scale atmospheric simulations, data assimilation (DA) methods, suited to this micrometeorological problem, could be applied to take benefit from these available observations.So far, DA methods have been mainly developed for large-scale meteorology and employed to correct the initial conditions (IC). In order to broaden the application scope of DA to micrometeorology, existing DA methods must be adapted to be able to correct the BC instead of IC.Two of the existing DA methods seem compatible with computational fluid dynamics (CFD) models used for micrometeorology over complex geometries: the back and forth nudging (BFN) algorithm and the iterative ensemble Kalman smoother (IEnKS). We have adapted these two methods, from a theoretical perspective, so as to include the BC in the control variables. The performances of the adapted versions of the BFN algorithm and the IEnKS have first been assessed with a simplified, 1D model of atmospheric flow with two layers, based on the shallow-water equations. The BFN algorithm and the IEnKS have then been tested in 2D and 3D with the atmospheric module of the open-source CFD model Code_Saturne.The first study case with Code_Saturne corresponds to a real application of wind resource assessment in a mountainous region with steep topography where three meteorological masts have been installed during a few months and provide in situ wind observations. The second case is a study of pollutant dispersion in an urban area, based on the measurements of wind and pollutant concentration coming from the “Mock Urban Setting Test” field campaign carried out in the USA. In this second case, the turbulence is also included in the BC and thus in the control variables. For both studies, some observations are assimilated and the remaining ones are used to validate the results.The experiences performed for the wind resource assessment study have revealed that the CFD models present too strong nonlinearities (flow recirculation after obstacles) for the BFN algorithm, which is based on a linearity assumption. However, both cases have shown the ability of the IEnKS to reduce the error and the uncertainty of the BC by assimilating a few observations, in operationally affordable conditions. Consequently, the simulated wind fields with Code_Saturne are also closer to the validation observations and the confidence intervals are reduced. Eventually, the IEnKS allows, in one case to estimate the wind potential, and in the other case to build the pollution maps, with much more exactitude and accuracy., La qualité de l’air est un enjeu sanitaire et environnemental majeur. Par ailleurs, l'estimation précise des potentiels éoliens est la source d’importantes retombées économiques et environnementales. Pour étudier ces deux sujets, il est nécessaire de reconstituer précisément les champs de vent locaux grâce à des modèles numériques de micrométéorologie. Ces simulations sont extrêmement sensibles aux conditions météorologiques aux limites du domaine d’étude. Jusqu’à présent, les conditions aux limites (CL) étaient estimées à partir de simulations à plus grande échelle, qui fournissent des informations peu adaptées à l’utilisation à l'échelle locale car imprécises, voire incomplètes. Par conséquent, la méconnaissance des CL représente une source majeure d’erreur et d’incertitude dans les études micrométéorologiques.Les sites susceptibles d’accueillir un parc éolien et les environnements bâtis (quartiers urbains ou sites industriels) peuvent être équipés d’instruments de mesures météorologiques ou de concentration de polluants. Les observations qu’ils fournissent constituent une seconde source d’information, jusqu’à ce jour peu exploitée pour les études micrométéorologiques. En effet, les mesures in situ sont perturbées par la géométrie complexe des sites étudiés. Afin d'améliorer la précision des CL et donc des simulations atmosphériques à l'échelle locale, des méthodes d'assimilation de données (AD) adaptées à cette problématique pourraient permettre de mettre à profit les observations disponibles.Jusqu’à présent, les méthodes d’AD ont été principalement développées pour la météorologie à grande échelle et ont donc surtout été utilisées pour corriger les conditions initiales (CI). Afin d'élargir le champ d'application de l’AD à la micrométéorologie, il faut adapter les méthodes existantes pour qu'elles permettent de corriger les CL plutôt que les CI.Deux méthodes d’AD semblent compatibles avec les modèles de mécanique des fluides (CFD) utilisés pour la micrométéorologie en géométrie complexe : l’algorithme de nudging direct et rétrograde (BFN) et le lisseur de Kalman d’ensemble itératif (IEnKS). Nous avons adapté ces deux méthodes d’un point de vue théorique pour inclure les CL dans les variables de contrôle. Les performances des versions adaptées du BFN et de l'IEnKS ont tout d'abord été étudiées avec un modèle simplifié d’écoulement atmosphérique à deux couches en 1D, basé sur les équations de Saint-Venant. Le BFN et l’IEnKS ont ensuite été testés en 2D puis 3D avec le module atmosphérique du modèle open-source de CFD Code_Saturne.Le premier cas d’étude avec Code_Saturne correspond à une application réelle d’estimation de potentiel éolien dans une région montagneuse au relief très accidenté où trois mâts de mesure fournissent des observations de vent. Le second cas correspond à une étude de dispersion de polluants en milieu urbain, basé sur les mesures de vent et de concentration provenant de la campagne « Mock Urban Setting Test » aux États-Unis. Dans ce second cas, la turbulence est également incluse dans les CL. Dans les deux études, une partie des observations est utilisée pour l’assimilation et le reste pour la validation des résultats.Les expériences menées sur le premier cas ont révélé que les modèles de CFD présentent des non-linéarités trop fortes (recirculations derrière les obstacles) pour l’algorithme de BFN, fondé sur une hypothèse de linéarité. L'étude de cette méthode n'a donc pas été poursuivie. En revanche, les deux études ont montré la capacité de l'IEnKS à réduire l'erreur et l'incertitude sur les CL grâce à l'assimilation d'une petite dizaine d'observations, en un nombre raisonnable de calculs. Par suite, les champs de vent simulés sont également plus proches des observations de validation et les intervalles de confiance sont réduits. Finalement, l'IEnKS permet d'estimer le potentiel éolien, dans un cas, et les concentrations en polluant, dans l'autre, avec beaucoup plus de précision et d'exactitude.

Capturing the effects of the complex processes of chemical aging of biogenic secondary organic aerosol (SOA) in chemical transport models (CTMs) has been challenging. Recent laboratory results from atmospheric simulation chambers are used in this study to develop a parameterization for biogenic SOA formation as a result of aging for use in CTMs using the Volatility Basis Set framework. This parameterization was implemented in PMCAMx which was then applied over the eastern United States to simulate summertime conditions. Using the base case parameterization of monoterpene SOA chemical aging resulted in modest increases (17–21%) in predicted domain average biogenic SOA. An alternative parameterization was developed fitting the same laboratory results, but assuming higher volatility products of chemical aging reactions. Use of this parameterization resulted in small increases (1–4%) of the predicted biogenic SOA. The PMCAMx predictions in sites where most of the SOA was biogenic were evaluated against measurements from the EPA IMPROVE network in July 2001 and during the Southern Oxidant and Aerosol Study in June 2013. The differences in the model performance were modest and mixed, a result consistent with the relatively small effect of the proposed parameterization on total organic aerosol levels.

Carbonyls play an important role in atmospheric chemistry due to their formation in the photooxidation of biogenic and anthropogenic volatile organic compounds and their high atmospheric reactivity. The Cl-initiated kinetics of two α-diketones (2,3-pentanedione (PTD) and 2,3-hexanedione (HEX)) have been determined as well as the OH + HEX rate constant using atmospheric simulation chamber experiments and the relative rate method. Up to three different reference compounds were used to assess robust results. The following rate constants (in cm3 molecule−1 s−1) have been obtained at 298 K: k(Cl + PTD) = (1.6 ± 0.2) × 10−11, k(Cl + HEX) = (8.8 ± 0.4) × 10−11, and k(OH + HEX) = (3.6 ± 0.7) × 10−12 with a global uncertainty of 30%. The present determinations of Cl- and OH- reaction rate constants for HEX constitute first measurements. Using the present measurements, a recently improved structure–activity relationship for Cl + ketone reactions has been updated by introducing an F(–COCO–) factor of 8.33 × 10−4. Atmospheric lifetime calculations indicate that chlorine-initiated oxidation may be a significant α-diketone sink in the marine-boundary layer or in places where high Cl concentrations may be found.

A way is substantiated for detecting new large-scale vortex instability in the tropical atmosphere. The instability may occur several hours or even several dozens of hours before the formation of a tropical depression or tropical storm. The diagnosis of instability was developed on the basis of data from idealized cloud-resolving atmospheric simulation for tropical cyclogenesis. It is suggested how the evolving instability may be traced by combining high-resolution numerical modeling and GOES Imagery. As an illustration, it is speculated and discussed that the instability may have emerged in future Hurricane Isaias (2020) when it had a status of Potential Tropical Cyclone for 36 hours before it was diagnosed as Tropical Storm.

Introduction: Air pollution (AP) represents the largest environmental risk for health. Such considerations however rely on the static quantification of only a few individual components of AP, without considering their interactions, chemical reactivity and synergistic toxicity. We therefore developed an innovative approach to analyze the health effects of “real life” model atmospheres at the preclinical level. Here, we report the first results of the feasibility study. Methods: A realistic atmosphere, representative of a 2017 pollution event in Paris, was generated (CESAM atmospheric simulation chamber - cesam.cnrs.fr). The chamber was connected to stalling cabinets where mice were exposed during 6 or 48 hours. Lungs, spleen, adipose tissue, heart, mesenteric ganglions were then harvested to address the expression of detoxification and antioxidant genes, as well as total cell count (TCC) and inflammatory cytokines expression in BAL fluid Results: The atmosphere contained 57.3 µg/m3 particulate matter, 114±11 ppb NO2 and 242±101 ppb O3. No mortality and no weight loss was observed. Increased expression of Ahr, Cyp1a1, Hmox1 and NQO1 was detected in the lungs, and increased TCC and KC concentrations in the BAL. Interestingly, we found extra pulmonary modifications; increased expression of Ahr, Cyp1a1, Hmox1 and NQO1 in the spleen, Hmox1, Cyp1a1 and Cyp1b1 in ganglions, and Hmox1 in the adipose tissue and heart. Limited modifications were detected after 6h. Conclusion: These preliminary results demonstrate the feasibility of our innovative experimental approach, which represents a versatile tool to get a better understanding of AP impacts on health.

International audience; Since the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in March 2011, atmospheric simulation models have improved our understanding of the atmospheric behavior of radionuclides. Model intercomparisons provide valuable and useful information for evaluating the validity and variability of individual model results. In this study, we compared results of seven atmospheric transport models used to simulate 137Cs released from the FDNPP to the atmosphere. All model results used in this analysis had been submitted for a model intercomparison project of the Science Council of Japan (2014, http//www.scj.go.jp/en/report/index.html). Here we assessed model performance by comparing model results with observed hourly atmospheric concentrations of 137Cs, with a particular focus on nine plumes over the Tohoku and Kanto regions. The intercomparison results showed that model performance in reproducing 137Cs concentrations was highly variable among different models and plumes. In general, models better reproduced plumes that passed over many observation stations. The performance among the models was consistent with the simulated wind fields and the source terms used. We also assessed model performance in relation to accumulated 137Cs deposition. Simulated areas of high 137Cs deposition were consistent with the simulated 137Cs plume pathways, though the models that best simulated atmospheric 137Cs concentrations were different from those that best simulated deposition. The ensemble mean of all models consistently reproduced atmospheric 137Cs concentrations and deposition well, suggesting that use of a multimodel ensemble results in more effective and consistent model performance. ©2018. American Geophysical Union. All Rights Reserved.

Atmospheric simulation chambers are exploratory platforms used to study various atmospheric processes at realistic but controlled conditions. We describe here a new facility specifically designed for the research on atmospheric bio-aerosol as well as the protocols to produce, inject, expose and collect bio-aerosols. ChAMBRe (Chamber for Aerosol Modelling and Bio-aerosol Research) is installed at the Physics Department of the University of Genoa, Italy, and it is a node of the EUROCHAMP-2020 consortium. The chamber is made of stainless steel with a total volume of about 2.2 m3. The lifetime of aerosol particle with dimension from a few hundreds of nanometres to a few microns varies from about 2 to 10 h. Characteristic parts of the facility are the equipment and the procedures to grow, inject, and extract bacterial strains in the chamber volume while preserving their viability. Bacteria are part of the atmospheric ecosystem and have impact on several levels as: health related issues, cloud formation, and geochemistry. ChAMBRe will host experiments to study the bacterial viability vs. the air quality level, i.e. the atmospheric concentration of gaseous and aerosol pollutants. In this article, we report the results of the characterization tests as well as of the first experiments performed on two bacterial strains belonging to the Gram-positive and Gram-negative groups. A reproducibility at the 10 % level has been obtained in repeated injections and collection runs with a clean atmosphere, assessing this way the chamber sensitivity for systematic studies on bacterial viability vs. environmental conditions.

This study was designed to evaluate the global scientific output of simulation research in "meteorology and atmospheric sciences" for the past 16 years and to assess the characteristics of the atmospheric simulation research patterns, tendencies and methods in the papers, from leading countries and institutes. Data were based on the online version of Science Citation Index, Web of Science from 1992 to 2007. Articles referring to atmospheric simulation were assessed by exponential regression fitting the trend of publication outputs with r 2 = 0.9996, distribution of source countries, source institutes, source titles, author keywords, and keywords plus, and the four most cited articles in these years. By synthetic analysis of the three kinds of keywords, it was concluded that atmospheric simulation research related to "ozone", "climate", "circulation", "transport", "parameterization" and "assimilation" will be foci of atmospheric simulation research in the 21 st century.

A spectroscopic instrument based on an external cavity quantum cascade laser was developed for optical monitoring of dinitrogen pentoxide (N2O5) at the ppbv-level in a nocturnal tropospheric chemical reaction process in an atmospheric simulation chamber.

In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows to estimate the full Doppler spectrum, as well a melting scheme which allows to represent the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

The Weather Research and Forecasting (WRF) modelling system is designed and developed to be a flexible atmospheric simulation system. It produces the images to display the three days rainfall forecasts. Therefore, the rainfall monitoring system has been created to calculate the volume of accumulated rainfall within six consecutive days (three days forecast and three days after) by applying the image processing technology with WRF images outputs. This work aims to assist in flood disaster monitoring. The outcomes of this system are the list of province names that have the highest accumulated rainfall volumes by applying the erosion of image processing filter and the intersection and buffer spatial operations to the WRF images.

Climate models often underestimate the magnitude of extreme precipitation. We compare the performance of a high-resolution (∼0.25°) time-slice atmospheric simulation (1979–2005) of the Community Earth System Model 1.0 in representing daily extreme precipitation events against those of the same model at lower resolutions (∼1° and 2°). We find significant increases in the simulated levels of daily extreme precipitation over Europe, the United States, and Australia. In many cases the increase in high percentiles (>95th) of daily precipitation leads to better agreement with observational data sets. For lower percentiles, we find that increasing resolution does not significantly increase values of simulated precipitation. We argue that the reduced biases mainly result from the higher resolution models resolving more key physical processes controlling heavy precipitation. We conclude that while high resolution is vital for accurately simulating extreme precipitation, considerable biases remain at the highest available model resolutions.

In this paper, we propose a simple and tunable robust compensator for an Adaptive Optics system, based on the Robust Model Matching strategies. In order to evaluate the performance of the system, we made some laboratory experiments with the atmospheric simulation instruments. Experimental result shows that by using the designed controller, the performance of the system has improved significantly comparing with some conventional works.