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CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.

Resumo os impactos da precipitação na qualidade da água ao longo do rio Purus, localizado no estado do Amazonas, foi investigado por meio de dados de precipitação, estimada por satélites, e informações sobre a temperatura da água, condutividade, ph, turbidez, oxigênio dissolvido e sólidos suspensos totais, adquiridas em quatro diferentes áreas ao longo do rio. os resultados mostraram correlação negativa entre precipitação e turbidez e positiva entre precipitação e temperatura, condutividade, oxigênio dissolvido, sólidos suspensos totais e ph. o uso do solo, juntamente com o regime de precipitação, parecem ser os fatores principais que determinam a qualidade da água nos pontos de amostragem.PalavRas chaves: qualidade da água, Rio Purus, precipitação, ph, condutividade. Impacts of precipitation on the water quality of the Purus River abstRactThe impacts of precipitation on the water quality along the Purus River, located in the Brazilian State of the Amazonas, was investigated using data of precipitation estimated by satellite and information about water temperature, conductivity, ph, turbidity, dissolved oxygen and total suspended solids. The data were acquired in four different areas along the river. The results showed negative correlation between precipitation and turbidity. They also showed positive correlation between precipitation and temperature, conductivity, dissolved oxygen, total suspended solids and ph. The land use together with the rainfall regime seems to be the main sources of impact on the water quality around the sampling places.

The rainfall characteristics over the Brazilian Amazon were analysed using 3 yr of 3 h data from 24 rain gauges. During this period, areas in the eastern sector experienced up to 22% of rainy hours, while those in the southern sector recorded up to 7%. In the northern Amazon, rain tends to occur during the night, while in southern, central and central-western Amazon it occurs mainly in the afternoon. In contrast, over the eastern Amazon, rain occurs late at night and early in the morning. Harmonic analysis revealed an increase in the phase of the first harmonic phase from eastern towards central Amazon, suggesting that the rain propagates in that direction. The amplitude of the first and second harmonics revealed the existence of a relatively dry area inland about 500 km from the Atlantic coast. This area seems to be the limit for the inland penetration of systems originating at the coast. The phase of the first harmonic revealed small differences between the diurnal cycles of rainfall during the wet and dry seasons, suggesting that there is no difference between low-level circulations in either season. KEY WORDS: Amazon · Diurnal cycle · Rainfall · Precipitation · Rain gauge Resale or republication not permitted without written consent of the publisherClim Res 26: [139][140][141][142][143][144][145][146][147][148][149] 2004 noon, from about 15:00 to 19:00 h LST (Dai 2001). The phase of convective activity over land in the South and Central Americas, South and Central Africa, India and Borneo is generally from late afternoon to evening (Houze et al. 1981, Hendon & Woodberry 1993, Yang & Slingo 2001. Specifically over the eastern coast of the Amazon, it has been found that peaks of rainfall tend to occur at 05:00 h LST in Marajó Island and at 17:00 h LST in Belém (Kousky 1980). In the central Amazon, near the convergence between the Amazonas and Negro rivers and over the Reserva Florestal Ducke, located at 25 km from Manaus, peaks of precipitation occur at 12:00 and 15:00 h LST, respectively (Lloyd 1990, Cutrim et al. 2000.Despite the low rain-gauge density over the Amazon Basin, the pluviometers in that area are sufficient to allow evaluation of some rainfall characteristics and also to be very useful as ground truth for satellite applications. The main purpose of the present study is to analyse 3 yr of previously unavailable rain-gauge data over the Brazilian Amazon so as to increase knowledge of the diurnal variations of rainfall over this area. DATA AND ANALYSIS METHODThe nature of the diurnal rainfall cycle was established using harmonic analysis, which yields information about the amplitude and phase (timing) of the peak in a time series. The methodology followed is that outlined by Wilks (1995). Accordingly, rainfall is modelled at time t in a series y by the harmonic function:where y is the mean of the series, n is the period, C is the amplitude, φ is the phase and k is the harmonic number. The amplitude C is estimated by:(2) where A 1 = 2/n × Σy t cos(2πt/n) (3)The phase can then be derived...

It is known from previous studies that radar data assimilation can improve short-range forecasts of precipitation, mainly when radial wind and reflectivity are available. However, from the authors’ experience radar data assimilation, when using the three-dimensional variational data assimilation (3DVAR) technique, can produce spurious precipitation results and large errors in the position and amount of precipitation. One possible reason for the problem is attributed to the lack of proper balance in the dynamical and microphysical fields. This work attempts to minimize this problem by adding a large-scale analysis constraint in the cost function. The large-scale analysis constraint is defined by the departure of the high-resolution 3DVAR analysis from a coarser-resolution large-scale analysis. It is found that this constraint is able to guide the assimilation process in such a way that the final result still maintains the large-scale pattern, while adding the convective characteristics where radar data are available. As a result, the 3DVAR analysis with the constraint is more accurate when verified against an independent dataset. The performance of this new constraint on improving precipitation forecasts is tested using six convective cases and verified against radar-derived precipitation by employing four skill indices. All of the skill indices show improved forecasts when using the methodology presented in this paper.