Preliminary Tests on the Sensitivity of the FORAIR_IT Air Quality Forecasting System to Different Meteorological Drivers

Since 2017, the operational high-resolution air quality forecasting system FORAIR_IT, developed and maintained by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, has been providing three-day forecasts of concentrations of atmospheric pollutants over Europe and Italy, on a daily basis, with high spatial resolution (20 km on Europe, 4 km on Italy). The system is based on the Atmospheric Modelling System of the National Integrated Assessment Model for Italy (AMS-MINNI), which is a national modelling system evaluated in several studies across Italy and Europe. AMS-MINNI, in its forecasting setup, is presently a candidate model for the Copernicus Atmosphere Monitoring Service’s regional production, dedicated to European-scale ensemble model forecasts of air quality. In order to improve the quality of the meteorological input into the chemical transport model component of FORAIR_IT, several tests were carried out on daily forecasts of NO2 and O3 concentrations for January and August 2019 (representative of the meteorological seasons of winter and summer, respectively). The aim was to evaluate the sensitivity to the meteorological input in NO2 and O3 concentration forecasting. More specifically, the Weather Research and Forecasting model (WRF) was tested to potentially improve the meteorological driver with respect to the Regional Atmospheric Modelling System (RAMS), which is currently embedded in FORAIR_IT. In this work, the WRF chain is run in several setups, changing the parameterization of several micrometeorological variables (snow, mixing height, albedo, roughness length, soil heat flux + friction velocity, Monin–Obukhov length), with the main objective being to take advantage of WRF’s consistent physics in the calculation of both mesoscale variables and micrometeorological parameters for air quality simulations. Daily forecast concentrations produced by the different meteorological model configurations are compared to the available measured concentrations, showing the general good performance of WRF-driven results, even if performance skills are different according to the single meteorological configuration and to the pollutant type. WRF-driven forecasts clearly improve the model reproduction of the temporal variability of concentrations, while the bias of O3 is higher than in the RAMS-driven configuration. The results suggest that we should keep testing WRF configurations, with the objective of obtaining a robust improvement in forecast concentrations with respect to RAMS-driven forecasts.

SIMULAÇÃO NUMÉRICA DO DESASTRE DE ORIGEM NATURAL OCORRIDO EM JANEIRO DE 2011 NO MUNICÍPIO DE NOVA FRIBURGO, RJ, UTILIZANDO O MODELO BRAMS

O conceito de desastre de origem natural é definido como o produto de um evento de ordem natural inerente à dinâmica da Terra associadas à vulnerabilidade de uma região. Esta vulnerabilidade pode estar associada a fatores naturais, antrópicos ou a uma combinação destes. O ano de 2011 foi marcado pela ocorrência de um desastre de origem natural ocorrido na Região Serrana do Rio de Janeiro (RSRJ) resultando em cerca de 900 mortos e 300 mil pessoas atingidas. Na cidade de Nova Friburgo foram 420 vítimas fatais e cerca de 180 mil pessoas atingidas direta e indiretamente pelo desastre natural O presente artigo analisa o ambiente sinótico e de mesoescala que culminou no desastre natural na cidade de Nova Friburgo. Utilizou-se o modelo atmosférico Brazilian Regional Atmospheric Modelling System (BRAMS) para simular o comportamento da atmosfera no período de 11 a 14 de janeiro de 2011. Verificou-se a partir das imagens do satélite GOES-12, canal Temperatura Realçada, e das simulações do BRAMS, que as chuvas intensas que provocaram os desastres na RSRJ foram geradas pelo deslocamento de uma frente fria que se acoplou a Zona de Convergência de Umidade, organizando a Zona de Convergência do Atlântico Sul.

The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy

In this paper, we study the impact of lightning and radar reflectivity factor data assimilation on the precipitation VSF (very short-term forecast, 3 h in this study) for two severe weather events that occurred in Italy. The first case refers to a moderate and localized rainfall over central Italy that occurred on 16 September 2017. The second case occurred on 9 and 10 September 2017 and was very intense and caused damages in several geographical areas, especially in Livorno (Tuscany) where nine people died. The first case study was missed by several operational forecasts, including that performed by the model used in this paper, while the Livorno case was partially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System at Institute for Atmospheric Sciences and Climate of the Italian National Research Council), whose 3D-Var extension to the assimilation of radar reflectivity factor is shown in this paper for the first time. Results for the two cases show that the assimilation of lightning and radar reflectivity factor, especially when used together, have a significant and positive impact on the precipitation forecast. For specific time intervals, the data assimilation is of practical importance for civil protection purposes because it changes a missed forecast of intense precipitation (≥40 mm in 3 h) to a correct one. While there is an improvement of the rainfall VSF thanks to the lightning and radar reflectivity factor data assimilation, its usefulness is partially reduced by the increase in false alarms, especially when both datasets are assimilated.

Modelagem dos Recursos Eólicos sobre Moçambique Considerando um Cenário de Mudanças Climáticas

Resumo Este trabalho apresenta uma aplicação da técnica de redução de escala (dynamic downscaling) usando-se o modelo regional RAMS6.0 (Regional Atmospheric Modelling System) forçado por campos de saída do modelo de circulação global HadGEM2-ES, com objetivo de estimar o potencial eólico nas regiões de Moçambique considerando um cenário de mudanças climáticas definido pelo IPCC. Os resultados mostraram desempenho satisfatório do modelo RAMS6.0 na reprodução de padrões médios de campos dos ventos obtidos nas reanálises do CFSR e MERRA durante o período de 1985-2005. Os campos de ventos simulados a 10, 50 e 100 m de altura, sob condições do cenário de emissão RCP8.5 do IPCC, para o período de 2079-2099, mostraram-se com valores superiores em relação aos campos de ventos para o período de 1985-2005. Além disso, há evidências de um aumento na densidade de energia eólica nas regiões de Moçambique para o período de 2079-2099, particularmente durante o inverno nas regiões centro e sul do país.

Trajectory Modelling of Atmospheric Pollutants Associated with Aircraft Emissions for Air Quality Assessment

Aviation is suffering a large increase in recent years and as result there is a consequent increase in emissions of air pollutants. The highest exposure levels of air pollution in airports and near them are found in the Landing and Take-off (LTO) cycle responsible for negative impacts on air quality. The city of Rio de Janeiro, in the coastal region of the South East of Brazil, has two major airports; the International airport and one for domestic flights. Both are near the Guanabara Bay (GB), in Metropolitan Region of Rio de Janeiro (MRRJ). In this research, it was verified the pollutant trajectories emitted by these two airports using the Brazilian Regional Atmospheric Modelling System (BRAMS) to generate wind fields in the MRRJ. From the wind fields, 3D kinematic trajectories Lagrangian model was used to calculate the pollutant trajectories. Atmospheric instability indices were tested from the BRAMS simulations to verify the days with more stable atmospheric conditions in winter month. The Total Totals index (TT) was selected to be more appropriate for the purpose of this study. Obtained results showed that the cities of Rio de Janeiro and Duque de Caxias, in the western of the MRRJ, are critical points to be affected continually by pollutant transport due to the prevailing meteorological conditions, harming the air quality in the region. These models captured the influence of mesoscale and large-scale systems, showing the dependence of the trajectories of both systems related to the season and time of day. They are important tools in decision-making for the control of emissions, contributing to better management of urban air quality.

Three-model ensemble wind prediction in southern Italy

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

RELAÇÃO ENTRE A TEMPERATURA DA SUPERFÍCIE DO MAR E A CAMADA DE MISTURA OCEÂNICA SOB A PASSAGEM DE CICLONES EXTRATROPICAIS NO ATLÂNTICO SUDOESTE

Neste artigo investigou-se a importância da variação da camada de mistura oceânica (CMO) na temperatura da superfície do mar (TSM), sob a influencia de ciclones extratropicais atmosféricos. Um modelo simplificado de CMO oriundo do modelo HYCOM (Hybrid Coordinate Ocean Model), baseado no modelo de Kraus e Turner, foi inserido como uma sub-rotina do modelo BRAMS (Brazilian Regional Atmospheric Modelling System), para atualizar a TSM a cada passo de tempo no modelo atmosférico. A CMO-BRAMS caracterizou-se por estreitar durante as trajetórias das baixas pressões, embora não tenha indicado um significativo aprofundamento seguindo o anticiclone da retaguarda do sistema frontal. A TSM calculada pela CMO do BRAMS apresentou grande variação (1°C-5°C) nos instantes iniciais. Entretanto, uma vez ajustada houve pouca variação da TSM no decorrer do tempo (1,0°C-2,5°C), com o aprofundamento (estreitamento) da CMO associada à diminuição (aumento) à temperatura.

Evaluation of the Wind Power in the State of Paraíba Using the Mesoscale Atmospheric Model Brazilian Developments on the Regional Atmospheric Modelling System

This work aims to describe the wind power density in five sites in the State of Paraiba, as well as to access the ability of the mesoscale atmospheric model Brazilian developments on the regional atmospheric modeling system (BRAMS) in describing the intensity of wind in São Gonçalo Monteiro, Patos, Campina Grande, and João Pessoa. Observational data are wind speed and direction at 10 m high, provided by the National Institute of Meteorology (INMET). We used the numerical model BRAMS in simulations for two different months. We ran the model for rainy months: March and April. It was concluded that the BRAMS model is able to satisfactorily reproduce the monthly cycle of the wind regime considered, as well as the main direction. However the model tends to underestimate the wind speed.

Determinação e modelagem da taxa de consumo de biomassa queimada

O presente trabalho avalia o emprego da energia radiativa do fogo (ERF) para estimar as emissões de material particulado com diâmetro menor que 2,5µm (PM2,5µm), a partir da obtenção do coeficiente multiplicativo, que relaciona o consumo de biomassa com a ERF liberada. Para isto, foram utilizados dados provenientes dos produtos do MODIS (Moderate Resolution Imaging Spectroradiometer) e do produto derivado do satélite GOES (Geostationary Operational Environmental Satellite), para calcular o total de aerossóis emitidos para a atmosfera. O CCATT-BRAMS (Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modelling System) foi utilizado para estimar a concentração de PM2,5µm provenientes da queima de biomassa. Estes dados foram comparados com os dados de campo obtidos nos experimentos do LBA (Large Scale Biosphere-Atmosphere) SMOCC (Smoke, Aerosols, Clouds, rainfall, and Climate) e RaCCI (Radiation, Cloud, and Climate Interactions). A estimativa da emissão de PM2,5µm (µg.m-3) apresentou uma correlação com os dados do SMOCC/RaCCI superiores a 92%. Ainda, constatou-se que o consumo máximo diário pode exceder 5 Tg (milhões de toneladas), com uma média diária de 2,1 Tg. O método resultante das análises de laboratório permitiu estimar a biomassa consumida em 0,28 ± 0,01 Pg (10(15) g) para a América do Sul, entre Julho e Novembro de 2002.

Avaliação dos prognósticos de precipitação simulada pelo modelo BRAMS na Amazônia Ocidental na estação chuvosa

O objetivo deste estudo é avaliar o modelo de previsão numérica do tempo BRAMS (Brazilian Regional Atmospheric Modelling System), a partir da comparação entre os valores preditos e os observados (dados do NCEP/NOAA (National Centers of Environmental Predictions/ National Oceanic and Atmospheric Administration) e do satélite TRMM (Tropical Rainfall Measuring Mission)). O modelo foi assimilado com dados do modelo global do NCEP/NOAA e do CPTEC/INPE. Foram realizadas comparações entre os valores preditos e os observados através da raiz do erro quadrático médio (RMSE) e do erro médio (ME) para os prognósticos de precipitação para os horizontes de 24, 48, 72 e 96 horas, do período de novembro de 2008 a março de 2009. Os resultados mostraram que o modelo BRAMS teve uma performance melhor quando assimilado com dados do modelo global do NCEP/NOAA comparado com as saídas a partir das assimilações do modelo global do CPTEC/INPE.