Evaluation of Subseasonal Precipitation Simulations for the Sao Francisco River Basin, Brazil

Water conflicts have been a significant issue in Brazil, especially in the Sao Francisco River basin. Subseasonal forecasts, up to a 60-day forecast range, can provide information to support decision-makers in managing water resources in the river basin, especially before drought events. This report aims to evaluate 5-year mean subseasonal simulations generated by the Eta regional model for the period from 2011 to 2016 and assess the usefulness of this information to support decision-making in water resource conflicts in the Sao Francisco River basin. The capability of the Eta model to reproduce the drought events that occurred between the years 2011 and 2016 was compared against the Climate Prediction Center Morphing (CMORPH) precipitation data. Two sets of 60-day simulations were produced: one started in September (SO) and the other in January (JF) of each year. These months were chosen to evaluate the model’s capability to reproduce the onset and the middle of the rainy seasons in central Brazil, where the upper Sao Francisco River is located. The SO simulations reproduced the observed spatial distribution of precipitation but underestimated the amounts. Precipitation errors exhibited large variability across the subbasins. The JF simulations also reproduced the observed precipitation distribution but overestimated it in the upper and lower subbasins. The JF simulations better captured the interannual variability in precipitation. The 60-day simulations were discretized into six 10-day accumulations to assess the intramonthly variability. They showed that the simulations captured the onset of the rainy season and the small periods of rainy months that occurred in these severe drought years. This research is a critical step to indicate subbasins where the model simulation needs to be improved and provide initial information to support water allocation in the region

Weather and climate extreme events in a changing climate

This chapter assesses changes in weather and climate extremes on regional and global scales, including observed changes and their attribution, as well as projected changes. The extremes considered include temperature extremes, heavy precipitation and pluvial floods, river floods, droughts, storms (including tropical cyclones), as well as compound events (multivariate and concurrent extremes). The assessment focuses on land regions excluding Antarctica

Climatologia da precipitação no município do Rio de Janeiro Precipitation climatology of the city of Rio de Janeiro

Uma climatologia preliminar da precipitação no município do Rio de Janeiro é elaborada utilizando-se 10 anos de dados observados na rede de 30 postos pluviométricos da Fundação Geo-Rio. A distribuição espacial do total pluviométrico anual médio mostra que os máximos concentram-se junto aos três maciços existentes na cidade: na Serra da Carioca (2200 mm) na Serra do Mendanha (1400 mm) e na Serra Geral de Guaratiba (1200 mm). Tais valores reduzem-se em direção às planícies, sendo um mínimo de 900 mm observado na Zona Norte da cidade. A estação Sumaré destaca-se por seus elevados índices pluviométricos durante todo o ano, especialmente em setembro quando a precipitação média mensal (297,5 mm) chega a ser cerca de sete vezes maior do que a dos postos localizados na Zona Norte. No Sumaré são observados em média 119 dias de chuva ao ano, enquanto, por exemplo, na Penha ocorre chuva em apenas 86 dias. A análise dos eventos de chuvas intensas indicou que 77% dos 160 casos selecionados, foram provocados por sistemas frontais, que ocorrem durante todo o ano, com menor freqüência no inverno. Eventos associados à Zona de Convergência do Atlântico Sul (13%) e sistemas convectivos de mesoescala (8%) predominam no verão. Chuvas intensas geradas por efeito de circulação marítima ocorreram em apenas 2% dos casos.<br>A preliminary 10-year precipitation climatology of Rio de Janeiro is elaborated by means of the Geo-Rio Foundation rain gauge network. The spatial distribution of annual precipitation shows that the maxima coincide with the three hills in the city: Carioca (2200 mm), Mendanha (1400 mm) and Geral de Guaratiba (1200 mm). The precipitation values decrease toward the plain, with minimum values in the Northern Zone. The precipitation is greater at the Sumaré gauge than in all the other places throughout the year, especially in September when the monthly mean precipitation (297.5 mm) is seven times greater than the precipitation in other Northern Zone stations. For example, rain occurs 119 days per year at Sumaré; at Penha it occurs only 86 days per year. The anaylsis of the intense events shows that 77% of the 160 selected events were caused by frontal systems, which occur throughout the year, though less frequently in winter. South Atlantic Convergence Zone events (13%) and Mesoscale Convective Systems (8%) occurred predominantly in summer. Rainfall caused by a sea breeze circulation occurred only in 2% of cases

Indicadores de turbulência a partir de previsões do modelo regional ETA Turbulence index from ETA model predictions

A turbulência em ar claro (Clear Air Turbulence - CAT), que ocorre freqüentemente próximo à região de corrente de jato, geralmente em altitudes entre 10.000 e 12.000 m, pode provocar sérios riscos para a aviação. Desta forma, previsões acuradas desse fenômeno contribuem na prevenção de acidentes aéreos e desconforto durante o vôo. Indicadores capazes de detectar esse fenômeno, como turbulência Brown (fim), Ellrod (ETI) e o de número de Richardson (Ri) foram calculados a partir das saídas do modelo regional ETA. As previsões de tais indicadores são avaliadas para 2 eventos de 24 de junho de 2003 e de 17 de agosto de 2006, e confrontadas com as informações contidas nas cartas de tempo significativo SIGWX. Os resultados mostram que os três indicadores de turbulência apresentaram boa correlação com as cartas SIGWX. O estudo mostrou a utilidade das previsões do modelo ETA para ajudar a entender o mecanismo da turbulência e para indicar a ocorrência do fenômeno com maior antecedência, por exemplo: 48h ou 72h comparado às 24h de antecedência das cartas SIGWX.<br>The Clear Air Turbulence (CAT) which is frequently observed near jet stream regions, usually in the layer between 10,000 and 12,000 m, may cause serious damages to aviation, reaching airplanes without warning. Therefore, predictions of this phenomenon can help to prevent physical damages and discomfort for the crew and passengers. Numerical weather prediction models have been used as powerful tools for operational forecasts of this phenomenon, by application of some indices in the determination of the turbulence areas. In this work, the Brown, Ellrod and Richardson number indices, calculated from ETA model outputs, are used to detect turbulence. The verification was accomplished for 2 events on 24 June 2003 and 17 August 2006 and was based on SIGWX charts. The results show that the three indices correlated well with SIGWX charts. This study showed that the use of ETA model forecasts could help to understand the mechanism of turbulence and to increase the forecast lead time to about 48h or 72h, as compared to 24-h forecast SIGWX maps