Extreme precipitation often persists for multiple days with variable duration but has usually been examined at fixed duration. Here we show that considering extreme persistent precipitation by complete event with variable duration, rather than a fixed temporal period, is a necessary metric to account for the complexity of changing precipitation. Observed global mean annual‐maximum precipitation is significantly stronger (49.5%) for persistent extremes than daily extremes. However, both globally observed and modeled rates of relative increases are lower for persistent extremes compared to daily extremes, especially for Southern Hemisphere and large regions in the 0‐45°N latitude band. Climate models also show significant differences in the magnitude and partly even the sign of local mean changes between daily and persistent extremes in global warming projections. Changes in extreme precipitation therefore are more complex than previously reported, and extreme precipitation events with varying duration should be taken into account for future climate change assessments.

O objetivo deste estudo foi avaliar as estimativas de precipitação mensal fornecidas por duas fontes (algoritmo 3B43_V6 e Universidade de Delaware) para o Estado do Rio Grande do Norte, no período de 1998 a 2008. Utilizaram-se técnicas estatísticas baseadas em coeficiente de correlação linear e em índices de desempenho extraídos de uma tabela de contingência 2x2. Na análise, consideraram-se diferentes regimes pluviométricos, que são função da localização geográfica e do tipo de cobertura do solo. Constatou-se que o algoritmo 3B43_V6 subestimou a precipitação para a região Litorânea e superestimou a precipitação observada em regiões mais áridas (Seridó e Oeste). A precipitação de Delaware apresentou médias similares às observações, mas verificaram-se algumas discrepâncias aparentemente associadas ao método de interpolação e ao espaçamento de grade. Os resultados sugerem que ambos os produtos são capazes de representar variabilidades médias da precipitação mensal no espaço e no tempo; porém, apresentaram deficiências em identificar os eventos mais intensos de precipitação.

Climate extreme events are becoming increasingly frequent worldwide, causing floods, drought, forest fires, landslides and heat or cold waves. Several studies have been developed on the assessment of trends in the occurrence of extreme events. However, most of these studies used traditional models, such as Poisson or negative binomial models. Thus, the main objective of this study is to use a space–time data counting approach in the modeling of the number of days with extreme precipitation as an alternative to the commonly used statistical methods. The study area is the Northeast Brazil region, and the analysis was carried out for the period between 1 January 1980 and 31 December 2010, by assessing the frequency of extreme precipitation represented by the R10 mm, R20 mm and R* indices.

The survival rate of mosquitoes is an important topic that affects many aspects of decision-making in mosquito management. This study aims to estimate the variability in the survival rate of Ae. aegypti, and climate factors that are related to such variability. It is generally assumed that the daily probability of mosquito survival is independent of natural environment conditions and age. To test this assumption, a three-year fieldwork (2005–2007) and experimental study was conducted at Fortaleza-CE in Brazil with the aim of estimating daily survival rates of the dengue vector Aedes aegypti under natural conditions in an urban city. Survival rates of mosquitoes may be age-dependent and statistical analysis is a sensitive approach for comparing patterns of mosquito survival. We studied whether weather conditions occurring on a particular day influence the mortality observed on that particular day. We therefore focused on the impact of daily meteorological fluctuations around a given climate average, rather than on the influence of climate itself. With regard to survival time, multivariate analyses using the stepwise logistic regression model, adjusted for daily temperature, relative humidity, and saturated vapor pressure deficit (SVPD), suggest that age, the seasonal factor, and the SVPD were the most dependent mortality factors. Similar results were obtained using the Cox proportional hazard model, which explores the relationships between the survival and explanatory variables.

It is generally assumed that the daily probability of survival of mosquitoes is independent of age. To test this assumption we have conducted a three-year experimental fieldwork study (2005–2007) at Fortaleza-CE in Brazil, determining daily survival rates of the dengue vector Aedes aegypti (L.). Survival rates of adult Ae. aegypti may be age-dependent and the statistical analysis is a sensitive approach for comparing patterns of mosquito survival. The mosquito survival data were better fit by a Weibull survival function than by the more traditionally used Gompertz or logistic survival functions. Gompertz, Weibull, or logistic survival functions often fit the survival, and the tails of the survival curves usually appear to fall between the values predicted by the three functions. We corroborate that the mortality of Ae. aegypti in semi-natural conditions may no more be considered as a constant phenomenon during the life of adult mosquitoes but varies according to the age and environmental conditions under a tropical climate. This study estimates the variability in the survival rate of Ae. aegypti and environmental factors that are related to such variability. The statistical analysis shows that the fitting ability, concerning the hazard function, was in decreasing order: Seasonal Cox, the three-parameter Gompertz, and the three-parameter Weibull, that was similar to the three-parameter logistic. The advantage of using the Cox model is that it is convenient for exploring the relationship between survival and several explanatory variables. The Cox model has the advantage of preserving the variable in its original quantitative form and of using a maximum of information. The survival analyses indicate that mosquito mortality is both age- and environment-dependent.