Homogeneidade de séries climatológicas em Minas Gerais Homogeneity of climatological series in Minas Gerais

Os dados climáticos são de extrema importância nas diversas atividades humanas, por fornecerem muitas informações relativas ao meio ambiente e aos impactos nele decorrentes. Portanto, há necessidade de informações meteorológicas estatisticamente homogêneas visto que uma série temporal não homogênea pode comprometer a análise e a interpretação desses dados. Assim, este trabalho teve como objetivo estudar metodologias para avaliar a homogeneidade de séries de dados de temperaturas máximas e mínimas no Estado de Minas Gerais. A análise de homogeneidade foi feita por meio de três testes de identificação de pontos de descontinuidade nas séries temporais: Teste de Homogeneidade Normal Padrão (SNHT), teste de Pettitt e teste Buishand. Os testes apresentaram resultados muito similares sendo que a maior parte das séries mensais de temperatura foi considerada homogênea. As heterogeneidades ocorreram na década de 1990, principalmente em torno de 1997.<br>Climatic data are extremely important in many human activities; they provide much information about the environment and its impacts. So there is a need for weather data information, statistically homogeneous, because heterogeneity can compromise any time series analysis and interpretations of such data. Thus, this work aimed to study methodologies for assessing the homogeneity of data sets of maximum and minimum temperatures in the state of Minas Gerais, Brazil. The analysis of homogeneity was carried out by means of three tests for the identification of points of discontinuity in the series: Standard Normal Homogeneity Test (SNHT), Pettitt test and the Buishand test. The results of the tests were very similar, with most of the monthly series of temperature were considered homogeneous. Heterogeneities occurred in the 1990s, especially around 1997

Analysis of mid-twentieth century rainfall trends and variability over southwestern Uganda

A methodology has been applied to investigate the spatial variability and trends existent in a mid-twentieth century climatic time series (for the period 1943–1977) recorded by 58 climatic stations in the Albert–Victoria water management area in Uganda. Data were subjected to quality checks before further processing. In the present work, temporal trends were analyzed using Mann–Kendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Results revealed that 53 % of stations have positive trends where 25 % are statistically significant and 45 % of stations have negative trends with 23 % being statistically significant. Very strong trends at 99 % significance level were revealed at 12 stations. Positive trends in January, February, and November at 40 stations were observed. The highest rainfall was recorded in April, while January, June, and July had the lowest rainfall. Spatial analysis results showed that stations close to Lake Victoria recorded high amounts of rainfall. Average annual coefficient of variability was 19 %, signifying low variability. Rainfall distribution is bimodal with maximums experienced in March–April–May and September–October–November seasons of the year. Analysis also revealed that PCI values showed a moderate to seasonal rainfall distribution. Spectral analysis of the time components reveals the existence of a major period around 3, 6, and 10 years. The 6- and 10-year period is a characteristic of September–October–November, March–April– May, and annual time series.http://link.springer.com/journal/704hb201