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A mancha foliar da Gala, causada por Colletotrichum spp, é uma doença da macieira tipicamente brasileira. Relatada pela primeira vez no Paraná, em 1983 (1), disseminou-se por todas as regiões do Brasil onde a macieira é cultivada. Em Santa Catarina, a MFG se estabeleceu no ciclo 1988/89, porém, até ociclo 1996/97, ficou restrita às regiões mais quentes, com altitude inferior a 1.200m. Atualmente, o controle da MFG é realizado exclusivamente com aplica-ções de fungicidas a cada cinco a dez dias, ou a cada 25mm de chuva, durante os meses que antecedem a colheita da maçã. Esta prática aumenta o custo de produção e a probabilidade de resíduo de fungicidas nos frutos.

The paper presents approach used for the development of the forecasting system of extreme hydro-meteorological events in the region of the Sea of Azov. Due to numerous dangerous extreme events that occurred in the beginning of XXI century the issue of creation such system has become very relevant and important. The forecasting system, named EX-MARE, was started developing in 2014 as a complex of mathematical models. For each type of hydro-meteorological events, the modeling component was designed. The EX-MARE system is based on a scenario approach implied the consideration a variety of possible futures taking into account the existing uncertainty. Accurate extreme events estimation requires automated monitoring systems and longterm database application. In the paper, the detail description of the system components and the data sources is examined. Three case studies about the sea surges, flash flood and ice conditions researches demonstrate the application of the EX-MARE system and the benefits of its using. Further development of the EX-MARE system assumes adding data on exposure and vulnerability to perform the risk assessment, as well as focusing on multi-hazards exploring methodology.

This report briefly summarizes recent progress in storm surge forecasts, one of topics discussed during the fourth International Workshop on Tropical Cyclone Landfall Process (IWTCLP 4) held during 5-8 December, 2017. In the workshop, improvement of storm surge forecasting system was mainly discussed with relevance to the problem of estimating the impacts of tropical cyclone landfall.To deal with storm surges, accurate TC condition (predictions and forecasts) as input, reasonable storm surge predictions (with forecasting systems), and effective advisories/warnings (i.e. useful information products) are necessary. Therefore, we need to improve storm surge related matters systematically: input, prediction system, and effective information.This report tries to highlight recent progress in the field of storm surges in relation to three key points: improvement in storm surge forecasting models/system, TC conditions as input for storm surge predictions, and informative products for end users. Keywords: storm surges, tropical cyclone, forecast system, warning, landfall

Operational forecasting systems based on chemical transport models (CTMs) nowadays generally produce concentration maps with a resolution in the order of 2–5 km, very rarely exceeding the sub-kilometre scale. The main reason for this restriction is the prohibitive computing cost that a simulation covering an entire country would have if set-up with a resolution in the order of meters. In this paper a hybrid forecast system, relying on the WRF-Chem model coupled with the PMSS Lagrangian modelling suite, has been developed and applied for each day of February 2019, to predict hourly NO2 and NOx concentrations with a spatial resolution of 4 m, for the urban area of Modena (a city located in the central Po Valley). Simulated meteorological fields (temperature, wind speed and direction) were assessed at three urban stations, compliant with WMO standards, and modelled concentrations were compared with measurements at two urban air quality stations located at background and traffic sites. Results show that meteorological variables are well captured by the hybrid system and statistical performances are in line with the benchmark values suggested by the European Environmental Agency and with similar case studies focusing on the same area. Modelled NO2 and NOx concentrations, notwithstanding a slight underestimation mainly evident at urban traffic stations for NOx, present a large agreement with related observations. The NO2 Model Quality Objective, as defined by Fairmode guidelines, was met for both the urban stations and the other statistical indexes considered in the evaluation fulfilled the acceptance criteria for dispersion modelling in urban environment, for both NO2 and NOx concentrations. In the second section of the study, the population exposure to forecasted NO2 concentrations has been evaluated adopting a generic model of dynamic population activity. The population was distributed at hourly time steps in specific urban micro-environments at the same resolution of the concentration maps (4 m) and the short-term exposure has been computed as the product between the population density in each model cell and related surface NO2 concentrations. An infiltration factor was also applied to estimate indoor concentrations. The hybrid system was shown to be particularly suited for assessing short-term peak exposure in areas influenced by traffic emissions. On the other hand, due to the limited time spent by the population within traffic related environments, the long-term population exposure calculated by the hybrid system tends to be similar to the WRF-Chem stand-alone estimate.

Smoke from forest fires is a growing concern in Korea as forest structures have changed and become more vulnerable to fires associated with climate change. In this study, we developed a Korean forest fire smoke dispersion prediction (KFSDP) system to support smoke management in Korea. The KFSDP system integrates modules from different models, including a Korean forest fire growth prediction model, grid-based geographic information system (GIS) fuel loading and consumption maps generated by national forest fuel inventory data, and the Korean Weather Research and Forecasting Model, into a Gaussian plume model to simulate local- and regional-scale smoke dispersion. The forecast system is operated using grid-based fires and simulates a cumulative smoke dispersion of carbon monoxide (CO) and &lt, 2.5 &micro, m and &lt, 10 &micro, m particulate matter (PM2.5 and PM10, respectively) ground-level concentration contours at 30-min intervals during the fire in concert with weather forecasts. The simulated smoke dispersions were evaluated and agreed well with observed smoke spreads obtained from real forest fires in Korea, and the performance of the KFSDP system was also analyzed using &ldquo, what-if&rdquo, scenarios. This is the first study to develop an integrated model for predicting smoke dispersion from forest fires in Korea.

An externalised surface scheme like SURFEX allows computationally cheap offline runs. This is a major advantage for surface assimilation techniques such as the extended Kalman filter (EKF), where the offline runs allow a cheaper numerical estimation of the observation operator Jacobian. In the recent past an EKF has been developed within SURFEX for the initialisation of soil water content and soil temperature based on screen-level temperature and relative humidity observations. In this paper we make a comparison of the Jacobian calculated with offline SURFEX runs and with runs coupled to the atmospheric ALARO model. Comparisons are made with respect to spatial structure and average value of the Jacobian, gain values and increments. We determine the optimal perturbation size of the Jacobian for the offline and coupled approaches and compare the linearity of the Jacobian for these cases. Results show that the offline Jacobian approach gives similar results to the coupled approach and that it allows for smaller perturbation sizes that better approximate this linearity assumption. We document a new case of non-linearities that can hamper this linearity assumption and cause spurious 2Δ t oscillations in small parts of the domain for the coupled as well as offline runs. While these oscillations do not have a detrimental effect on the model run, they can introduce some noise in the Jacobian at the affected locations. The oscillations influence both the surface fluxes and the screen-level variables. The oscillations occur in the late afternoon in summer when a stable boundary layer starts to form near the surface. We propose a filter to remove the oscillations and show that this filter works accordingly.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Diseases and environment are closely related, especially with regard to air temperature and relative humidity. The weather data tend to follow a daily pattern of temporal variation, which derives mainly from the daily variation of the surface radiation balance. Based on this, this study aimed to make a qualitative and quantitative description of the database of the Automatic Meteorological Station of the Instituto Nacional de Meteorologia (INMET) in Santa Maria, RS, determine the hours of greatest frequency of occurrence of daily extreme air temperatures in Santa Maria, develop models to estimate hourly values of air temperature (T) and relative humidity (RH), based on values measured in "UTC standard times" and on the daily minimum air temperature and to determine the risk of fungal diseases occurrence during the developmental cycle of potato in different planting dates, using the Blitecast forecasting system. Models were fitted to estimate air T and partial vapor pressure of water at different times of the day. RH was indirectly obtained from partial vapor pressure of water and saturation vapor pressure, calculated from estimated T values. The database of Principal Climatological Station of Santa Maria was transformed to an hourly estimated T and RH database and the Blitecast's calculated severity values (CSV) were obtained for 14 planting dates in 43 years. The automatic weather station of Santa Maria, RS, belonging to INMET, shows 90.1% of the days of flawless data records in 10 years, from 2002 to 2011. The minimum daily air temperature in Santa Maria occurs more frequently at 09AM UTC, corresponding to 6AM on local official time, from September to February. From March through August, this time is delayed, and its occurrence to be more frequent at 10 h UTC. The precision of the estimates ranged from 0.7 ºC to 1.5 ºC, with average deviation of 0.65 °C for T and 0.7 % to 1.2 %, with average deviation of up to 4% for RH depending on the time. Potato crops during the Fall growing season require on average 54% more fungicide applications compared to the Spring season. In the Spring growing season the most probable number of sprayings ranged from two to four and from six to seven in the Fall growing season. Potato crops planted in August and March were demanded a lower economic, ecological and farmer health cost in crop protection against late blight than earlier crops (July and February). Doenças e ambiente estão intimamente relacionados, especialmente no que se refere à temperatura e umidade relativa do ar. Os elementos meteorológicos tendem a seguir um padrão de variação temporal diária, que deriva principalmente da variação diária do balanço de radiação da superfície. Com base nisso, o objetivo desse trabalho foi descrever qualitativa e quantitativamente do banco de dados da Estação Meteorológica Automática do Instituto Nacional de Meteorologia de Santa Maria (INMET), determinar os horários de maior frequência de ocorrência das temperaturas extremas diárias do ar em Santa Maria, desenvolver modelos para estimativa dos valores horários de temperatura (T) e umidade relativa do ar (UR) e determinar o risco de ocorrência de requeima no ciclo de desenvolvimento da batata, em diferentes datas de plantio. Foram ajustados modelos analíticos para estimativa da T e da pressão parcial de vapor no ar nos diferentes horários do dia. A UR foi obtida indiretamente, com base nos valores de pressão parcial de vapor no ar estimados e nos valores de pressão de saturação de vapor no ar, calculados com base na T estimada. O banco de dados da Estação Climatológica Principal de Santa Maria foi transformado em um banco de dados horários estimados de T e UR e foram obtidos os valores de severidade calculada (VSC) pelo sistema Blitecast em 14 datas de plantio da batata em 43 anos agrícolas. A estação meteorológica automática de Santa Maria, RS, pertencente ao INMET, apresenta 90,1% dos dias sem falhas de registros de dados em 10 anos, de 2002 a 2011. A temperatura mínima diária do ar em Santa Maria ocorreu com maior frequência às 09 h UTC, correspondendo às 06 h no horário oficial local, nos meses de setembro a fevereiro. De março até agosto, esse horário é atrasado, sendo a sua ocorrência mais frequente às 10 h UTC. A precisão das estimativas variou de 0,7 oC a 1,5 oC, com desvio médio de até 0,65oC para T do ar e de 0,7 % a 1,2 %, com desvio médio de até 4 %, para UR, dependendo do horário. Cultivos de batata no período de safrinha necessitam, em média, de um número 54 % maior de aplicações de fungicida em relação ao período de safra. Na safra o número mais provável de pulverizações oscila entre duas e quatro e na safrinha entre seis e sete. Plantios de batata realizados em agosto e em março exigiram um menor custo econômico, ecológico e de saúde do produtor na proteção da cultura contra a requeima do que plantios mais precoces (julho e fevereiro).

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the originalMERRAestimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies. © 2011 American Meteorological Society. ispartof: Journal of Climate vol:24 issue:24 pages:6322-6338 status: published

This paper presents the Weather Forecast User-oriented System Including Object Nowcasting (WxFUSION), an integrated weather forecast system for air traffic. The system is currently under development within a new project named “Weather and Flying” under the leadership of the Institute of Atmospheric Physics (IPA) at the German Aerospace Center (DLR). WxFUSION aims at combining data from various sources, as there are weather observations, remote sensing, nowcasting and numerical model forecast data, in order to extract specific information on target weather objects like thunderstorms, icing, or areas with heavy snow fall. The target weather objects are pre-defined including user requirements. The paper gives a short overview on the concept of the system and on-going work.

Conselho Nacional de Desenvolvimento Científico e Tecnológico Potato is grown in Central Rio Grande do Sul State mainly by small farmers, which use weekly sprayings with fungicides, without taking into account if meteorological conditions favor or not Late Blight and other pathogens. Water deficit can affect potato development and growth, which may affect tuber yield and quality. Irrigation applied inadequality may favor diseases due to leaf wetning. Both leaf wetning high an relative humidity play an important role in epidemic events, favoring Late Blight (Phytophthota infestans), a pathogen with high potential of causing disease. The objective of this study was to determine the effect of different levels of irrigation on yield and occurrence of Late Blight in potato cv. Asterix in the area of influence of the Meteorological Station of Santa Maria. Two experiments were conducted at the experimental field, Crop science Department, Federal University of Santa Maria. One experiment was during spring, from 21/11/2005 (emergence) to 21/02/2006 (harvest). The second experiment was during fall, from 10/04 (emergence) to 13/07/2006. The experimental design was a complete randomized, with four replications. Each replication was a 5 m x 3,2 m plot with four rows. Plant spacing was 0,8 m x 0,3 m. Fungicides used to control Late Blight were mancozebe (Dithane NT 3,0 Kg ha-1), copper oxychloride (Cuprogarb 350 4 g l-1), pyraclostrobin + metiram (Cabrio Top 3,0 Kg ha-1). The Blitecast model was used to indicate the timing of spraying, by accumulating severity values (VS) of 0 (control), 18, 24, and 30. Sprinkling irrigation was used assuming 1,0 ETm, 0,75 ETm, 0,50 ETm and no irrigation. Results showed that in dry and high temperature periods, yield was affected by irrigation, mainly when crop water demand was plenty recharged with 100% ETm. During wet periods, yield was affected by the efficient of Late Blight control. The Blitecast model with a severity value of 18 (Bli18) was the most efficient for controlling Late Blight, compared to Bli24 and Bli30, as a tool for managing fungicides application. Irrigations applied at least every there days did not affect Late Blight incidure and development O cultivo da batata na região central do Estado do Rio Grande do Sul é realizado em sua maioria por pequenos produtores, que se utilizam, em geral, de calendários com aplicação semanal de fungicidas, não levando em consideração se as condições meteorológicas são favoráveis ou desfavoráveis para o desenvolvimento da requeima e outros patógenos da batata. A deficiência hídrica também pode afetar o desenvolvimento e o crescimento dessa cultura, o que se reflete na produtividade e na qualidade dos tubérculos, sendo a irrigação uma prática freqüente. Porém a irrigação realizada inadequadamente pode também favorecer o aparecimento de doenças devido ao molhamento foliar. Tanto o molhamento foliar quanto a umidade relativa do ar elevada desempenham um importante papel na epidemiologia, favorecendo a ocorrência da requeima causada por Phytophthora infestans (Mont.) De Bary, um patógeno de alto potencial destrutivo. O trabalho teve como objetivo determinar o efeito de diferentes níveis de irrigação na produtividade e ocorrência de requeima na cultura da batata, cultivar Asterix , na região de abrangência da Estação Meteorológica de Santa Maria. Foram realizados dois experimentos na área experimental do Departamento de Fitotecnia da Universidade Federal de Santa Maria, sendo o primeiro na primavera, no período de 21/11/2005 (emergência) a 21/02/2006 (colheita) e o segundo no outono de 2006, no período de 10/04 (emergência) a 13/07/2006 (colheita). O delineamento experimental utilizado foi o de blocos ao acaso com quatro repetições, sendo cada parcela composta de quatro fileiras de plantas com 5,0 m de comprimento e 3,2 m de largura. O plantio foi realizado conforme as técnicas recomendadas para a região, com espaçamento entre fileiras de plantas de 0,80 m e entre as plantas nas fileiras de 0,30 m. Para o controle da requeima da batata foram utilizados os fungicidas mancozebe (Dithane NT 3,0 kg ha-1 do produto comercial), oxicloreto de cobre (Cuprogarb 350 4 g l-1 do produto comercial), piraclostrobina + metiram (Cabrio Top 3,0 kg ha-1 do produto comercial). Foi utilizado o sistema Blitecast para determinar o momento da aplicação de fungicidas, através do acúmulo de valores de severidade (VS) igual a 0 (Test), 18, 24 e 30. Para fins de comparação, a irrigação foi realizada por aspersão, utilizando a dotação de 1,0 ETm, 0,75 ETm, 0,50 ETm e sem irrigação. Os resultados mostram que em períodos relativamente secos com temperatura alta, a produtividade foi influenciada pela irrigação, principalmente quando a necessidade hídrica da cultura foi plenamente atendida com a reposição de 100% da ETm. Em períodos úmidos, a produtividade foi influenciada pela eficiência no controle da requeima. O sistema Blitecast com acúmulo de 18 valores de severidade (Bli18) foi o mais eficiente em comparação com o Bli24 e o Bli30 para o controle da requeima da batata, como esquema de gerenciamento de aplicação de fungicidas. A irrigação realizada em intervalos de pelo menos três dias não teve influência significativa sobre a incidência e o desenvolvimento da requeima

Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Engenharia Oceânica, Escola de Engenharia, 2005. The atmospheric dynamics evidently is very complex. There are many macro and micron scales processes and meteorological variables involved in the atmospheric physical phenomena. The storms with electrical dischargesare distinguished, among these phenomena, by the damage consequences to the human beings, directly or indirectly. Many researchers have pursued the possibility of forecasting the occurrence of a storm with electrical discharges, principally in the last three decades. However, there are not improvements in forecast performance, mainly due to phenomenon complexity. The main objective of the present dissertation was to accomplish a study to determine the viability or not of constructing a forecast system of atmospheric electrical discharges from artificial intelligence techniques, specifically artificial neural networks (NN). The base of the system was constituted of numerical simulations results of the atmospheric dynamics obtained from the mesoscale model MM5. It was identified meteorological variables (outputs of MM5) that would have some correlation with the electrical discharges. These variables act as input in the NN, which generate the forecast, consisting in the number of electrical discharges that will reach the ground some posterior time to the relative time of the simulated atmospheric fields. The region chosen for this study includes the state of Rio de Janeiro, the south of Espírito Santo, the southeast of Minas Gerais and the AtlanticOcean. Besides possessing a detection system of electrical discharges, this region contains the most important concentration of oil platforms of Brazil, being strategic to better know the atmospheric behavior in this place. Before developing the forecast system based on NN, some comparative tests were made using the MM5 simulation results and GOES infrared imagery, in order to survey the model prognostic capability. The forecast system showed reasonable results, indicating that the NN application may be a promising way to the electrical discharge forecast. However, it is necessary a better investigation, mainly with relation to the accomplishment of others tests with a bigger set of electrical discharges real data. A dinâmica da atmosfera é evidentemente bastante complexa. Muitos são os processos físicos de macro e micro escalas e as variáveis meteorológicas envolvidos nos fenômenos atmosféricos. As tempestades com descargas elétricas destacam-se, dentre estes fenômenos, pelas conseqüências danosas causadas aos seres humanos, direta ou indiretamente. Diversos pesquisadores têm procurado investigar a possibilidade de prever a ocorrência de tempestades com descargas elétricas, principalmente nas úl timas três décadas, entretanto, progressos na performance da previsão ainda não foram alcançados devido à complexidade do fenômeno. O principal objetivo da presente dissertação foi realizar um estudo para determinar a viabilidade ou não de construir um sistema de previsão de descargas elétricas atmosféricas a partir de técnicas de inteligência artificial, mais precisamente redes neurais artificiais (RNA). A base do sistema constituiu-se de resultados de simulações numéricas da dinâmica atmosférica obtidos com o modelo de mesoescala MM5. Variáveis meteorológicas (saídas do MM5), que teriam alguma correlação com as descargas elétricas, foram identificadas e selecionadas como entradas na RNA, a qual gera a previsão, isto é, o número de descargas elétricas que atingirá o solo algum tempo posterior ao tempo relativo dos campos atmosféricos simulados. A região escolhida para este estudo, abrangendo o Estado do Rio de Janeiro, o sul do Estado do Espírito Santo, o sudeste do Estado de Minas Gerais e o Oceano Atlântico, além de possuir um sistema de detecção e monitoramento de descargas elétricas, contém a mais importante concentração de plataformas de petróleo do Brasil, sendo, portanto, estratégico conhecer melhor o seu comportamento atmosférico. Antes de desenvolver o sistema de previsão baseado em RNA, alguns testes comparativ os foram realizados usando resultados de simulação do MM5 e imagens infravermelhas de satélite geoestacionário, a fim de aferir a capacidade preditiva do modelo. O sistema de previsão apresentou resultados razoáveis, indicando que a aplicação da RNA é um cami nho promissor na previsão de descargas elétricas. Contudo, faz-se necessária uma mel hor investigação, principalmente quanto à realização de outros testes com um conjunto maior de dados reais de descargas elétricas.