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We used WRF-Chem to simulate ash transport from eruptions of Chile’s Calbuco volcano on 22–23 April 2015. Massive ash and SO2 ejections reached the upper troposphere, and particulates transported over South America were observed over Argentina, Uruguay, and Brazil via satellite and surface data. Numerical simulations with the coupled Weather Research and Forecasting–Chemistry (WRF-Chem) model from 22 to 27 April covered eruptions and particle propagation. Chemical and aerosol parameters utilized the GOCART (Goddard Chemistry Aerosol Radiation and Transport) model, while the meteorological conditions came from NCEP-FNL reanalysis. In WRF-Chem, we implemented a more efficient methodology to determine the Eruption Source Parameters (ESP). This permitted each simulation to consider a sequence of eruptions and a time varying ESP, such as the eruption height and mass and the SO2 eruption rate. We used two simulations (GCTS1 and GCTS2) differing in the ash mass fraction in the finest bins (0–15.6 µm) by 2.4% and 16.5%, respectively, to assess model efficiency in representing plume intensity and propagation. Analysis of the active synoptic components revealed their impact on particle transport and the Andes’ role as a natural barrier. We evaluated and compared the simulated Aerosol Optical Depth (AOD) with VIIRS Deep Blue Level 3 data and SO2 data from Ozone Mapper and Profiler Suite (OMPS) Limb Profiler (LP), both of which are sensors onboard the Suomi National Polar Partnership (NPP) spacecraft. The model successfully reproduced ash and SO2 transport, effectively representing influencing synoptic systems. Both simulations showed similar propagation patterns, with GCTS1 yielding better results when compared with AOD retrievals. These results indicate the necessity of specifying lower mass fraction in the finest bins. Comparison with VIIRS Brightness Temperature Difference data confirmed the model’s efficiency in representing particle transport. Overestimation of SO2 may stem from emission inputs. This study demonstrates the feasibility of our implementation of the WRF-Chem model to reproduce ash and SO2 patterns after a multi-eruption event. This enables further studies into aerosol–radiation and aerosol–cloud interactions and atmospheric behavior following volcanic eruptions.

This paper presents the observational, remote sensing, and model simulation used to analyze southern Brazil Antarctic ozone hole influence (SBAOHI) events that occurred between 2005 and 2014. To analyze it, we use total ozone column (TOC) data provided by a Brewer spectrophotometer (BS) and the OMI (Ozone Monitoring Instrument). In addition to the AURA/MLS (Microwave Limb Sounder) instrument, satellite ozone profiles were utilized with DYBAL (Dynamical Barrier Localization) code in the MIMOSA (Modélisation Isentrope du Transport Mésoéchelle de l’Ozone Stratosphérique par Advection) model Potential Vorticity (PV) fields. TOC has 7.0 ± 2.9 DU reductions average in 62 events. October has more events (30.7%). Polar tongue events are 19.3% in total, being more frequently observed in October (50% of cases), with medium intensity (58.2%), and in the stratosphere medium levels (55.0%). Already, polar filament events (80.7%) are more frequent in September (32.0%), with medium intensity (42.0%), and stratosphere medium levels (40.7%).

Ozone plays an important role in the Earth’s atmosphere. It is mainly formed in the tropical stratosphere and is transported by the Brewer–Dobson Circulation to higher latitudes. In the stratosphere, ozone can filter the incoming solar ultraviolet radiation, thus protecting life at the surface. Although tropospheric ozone accounts for only ~10%, it is a powerful GHG and pollutant, harmful to the health of the environment and living beings. Several studies have highlighted biomass burning as a major contributor to the tropospheric ozone budget. Our study focuses on the Natal site (5.40°S, 35.40°W, Brazil), one of the oldest ozone-observing stations in Brazil, which is expected to be influenced by fire plumes in Africa and Brazil. Many studies that examined ozone trends used the total atmospheric columns of ozone, but it is important to assess ozone separately in the troposphere and the stratosphere. In this study, we have used radiosonde ozone profiles and daily TCO measurements to evaluate the variability and changes of both tropospheric and stratospheric ozone separately. The dataset in this study comprises daily total columns of colocalized ozone and weekly ozone profiles collected between 1998 and 2019. The tropospheric columns were estimated by integrating ozone profiles measured by ozone sondes up to the tropopause height. The amount of ozone in the stratosphere was then deduced by subtracting the tropospheric ozone amount from the total amount of ozone measured by the Dobson spectrometer. It was assumed that the amount of ozone in the mesosphere is negligible. This produced three distinct time series of ozone: tropospheric and stratospheric columns as well as total columns. The present study aims to apply a new decomposition method named Empirical Adaptive Wavelet Decomposition (EAWD) that is used to identify the different modes of variability present in the analyzed signal. This is achieved by summing up the most significant Intrinsic Mode Functions (IMF). The Fourier spectrum of the original signal is broken down into spectral bands that frame each IMF obtained by the Empirical Modal Decomposition (EMD). Then, the Empirical Wavelet Transform (EWT) is applied to each interval. Unlike other methods like EMD and multi-linear regression (MLR), the EAWD technique has an advantage in providing better frequency resolution and thus overcoming the phenomenon of mode-mixing, as well as detecting possible breakpoints in the trend mode. The obtained ozone datasets were analyzed using three methods: MLR, EMD, and EAWD. The EAWD algorithm exhibited the advantage of retrieving ~90% to 95% of ozone variability and detecting possible breakpoints in its trend component. Overall, the MRL and EAWD methods showed almost similar trends, a decrease in the stratosphere ozone (−1.3 ± 0.8%) and an increase in the tropospheric ozone (+4.9 ± 1.3%). This study shows the relevance of combining data to separately analyze tropospheric and stratospheric ozone variability and trends. It highlights the advantage of the EAWD algorithm in detecting modes of variability in a geophysical signal without prior knowledge of the underlying forcings.

Abstract During the southern spring, a break of the polar vortex over the Antarctic continent frequently occurs. This results in the advection of ozone‐poor air mass (O3) to mid‐latitudes, characterizing the secondary effect of the Antarctic ozone hole (SEAOH). We present some distinct characteristics the eight greatest reductions of the total O3 column (TOC) over the central region of Rio Grande do Sul (RS, 29.5°S, 54°W), southern Brazil, between August and November from 2012 to 2016 and develop a full scalar diagnostic index of O3 negative anomalies for South America. For developing the index, mean values of the absolute potential vorticity, geopotential height, and wind components were obtained over moving grids with positive and negative O3 anomalies. It was then possible to develop statistical methods to obtain a diagnostic index of the SEAOH (Subantarctic O3 Index), as well as a diagnostic index of incursions of ozone‐poor air masses from the tropics (Subtropical O3 Index). The results show that TOC over the central region of RS, for the most intense O3 reduction episodes, is governed by a wide range of contributions from high and low isentropic levels. Significant interaction of air masses of polar and tropical origin via stratosphere–troposphere exchange was found. Finally, the Subantarctic O3 Index combined with the Subtropical O3 Index showed potential use for prediction centres and was skilful in detecting regions with the most negative O3 anomalies, mainly in the mid‐latitude region, but also in the subtropical region.

Recently, several real quantum devices have become available through the cloud. Nevertheless, they are expected to be very limited, in the near term, in the number and quality of the fundamental storage element, the qubit. Therefore, software quantum simulators are the only widely available tools to design and test quantum algorithms. However, the representation of quantum computing components in classical computers consumes a big amount of resources. This work describes how to model the main elements of quantum computing in a classical computer and depicts resource consumption using two popular quantum simulators. In the end, we discuss different approaches to overcome this problem.

Energy management focuses on improving the efficient use of resources and increasing energy access in a path towards a more sustainable society. In spite of the strategies that have been proposed to guarantee increased access to the energy resources at affordable costs, there are still challenges to ensure the conservation of the resources and the protection of the environment. In line with these objectives, Cloud Computing for Smart Energy Management project (CC-SEM) is a research effort for building an integrated platform for smart monitoring, controlling, and planning energy consumption and generation in urban scenarios. CC-SEM includes, firstly, the design of a low-cost IoT device capable of monitoring, operating, and controlling home appliances according to predefined rules. It was developed with the aim of automatically manage consumption. Secondly, an analysis of 5G Narrowband IoT as a suitable cellular technology for Smart Grid outage restoration and management message delivery was addressed. Thirdly, an analysis of domestic consumption patterns was carried out to help to predict home consumption, using literature measurements. Fourthly, within the context of electrical network simulation, a forecasting and performance evaluation methodology for the generation of individual photovoltaic systems is proposed. In summary, CC-SEM presents the research efforts to provide a set of tools for controlling home devices, planning/simulating scenarios of energy generation, and to propose advances in the communication infrastructure for transmitting the generated data.

During the last decades, researchers have developed novel computing methods to help viticulturists solve their problems, primarily those linked to yield estimation of their crops. This article aims to summarize the existing research associated with computer vision and viticulture. It focuses on approaches that use RGB images directly obtained from parcels, ranging from classic image analysis methods to Machine Learning, including novel Deep Learning techniques. We intend to produce a complete analysis accessible to everyone, including non-specialized readers, to discuss the recent progress of artificial intelligence (AI) in viticulture. To this purpose, we present work focusing on detecting grapevine flowers, grapes, and berries in the first sections of this article. In the last sections, we present different methods for yield estimation and the problems that arise with this task.

Resumo O monitoramento de longo prazo dos eventos de Influência do Buraco de Ozônio Antártico sobre o Sul do Brasil foi realizado no período de 35 anos entre 1979 e 2013 e calculada a climatologia e anomalias dos campos estratosféricos quando de sua ocorrência. Para isso, foram analisados os dados da coluna total de ozônio (CTO) obtidos através de Espectrofotômetros Brewer, instalados no Observatório Espacial do Sul - OES/CRS/INPE - MCTIC (29,4 °S; 53,8 °O; 488,7 m) e pelos instrumentos de satélite Total Ozone Mapping Spectrometer (TOMS) e Ozone Monitoring Instrument (OMI), além de parâmetros da reanálise II do NCEP/DOE (National Centers for Environmental Prediction/ Departament of Energy) e trajetórias retroativas do modelo HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory). A metodologia empregada mostrou-se eficaz na identificação de 62 eventos com uma redução média de -9,35 ± 2,93% no conteúdo de ozônio. Além disso, foi realizada a identificação do padrão de circulação estratosférica através de campos médios e anomalias da vorticidade potencial, vento e temperatura para os dias de ocorrência do fenômeno, sendo observado um padrão de deslocamento de onda, embebida dentro de uma ampla região de circulação ciclônica, com ventos predominantemente de sul é advectado em direção ao Sul do Brasil.