On the influences of the El Niño, La niña and Atlantic Dipole Paterni on the Amazonian Rainfall during 1960-1998

The influence of the large-scale climatic variability dominant modes in the Pacific and in the Atlantic on Amazonian rainfall is investigated. The composite technique of the Amazon precipitation anomalies is used in this work. The basis years for these composites arc those in the period 1960-1998 with occurrences of extremes in the Southern Oscillation (El Niño or La Niña) and the north/south warm (or cold) sea surface temperature (SST) anomalies dipole pattern in the tropical Atlantic. Warm (cold) dipole means positive (negative) anomalies in the tropical North Atlantic and negative (positive) anomalies in the tropical South Atlantic. Austral summer and autumn composites for extremes in the Southern Oscillation (El Niño or La Niña) and independently for north/south dipole pattern (warm or cold) of the SST anomalies in the tropical Atlantic present values (magnitude and sign) consistent with those found in previous works on the relationship between Amazon rainfall variations and the SST anomalies in the tropical Pacific and Atlantic. However, austral summer and autumn composites for the years with simultaneous occurrences of El Niño and warm north/south dipole of the SST anomalies in the tropical Atlantic show negative precipitation anomalies extending eastward over the center-eastern Amazon. This result indicates the important role played by the tropical Atlantic in the Amazon anomalous rainfall distribution.

Structure of Anopheles (Diptera: Culicidae) population in areas with different degrees of human settlement: Cantá - Roraima - Brazil

Malaria has still been one of the most important endemic diseases in the Amazonian region. This study presents the impact of human settlements on the structure of Anopheles population. Diversity, abundance, richness and distribution of the genus Anopheles were observed in two areas with different levels of human settlement in the Cantá city, Roraima State, Northern Brazil. The influence of the dry and rainy seasons on mosquito populations was also observed. Mosquito captures were performed between 6:00 and 10:00 pm during the dry (February and November) and rainy (May and August) seasons at four different sites of each area. Among the 11 species of Anopheles identified through the adults' characteristics, An. albitarsis s.l. (45.5%) and An. darlingi (19.2%) were the most abundant in the more intensively anthropized area while An. triannulatus (19.2%) was more common in the less modified area. Other species found were An. nuneztovari (10.9%), An. oswaldoi (2.0%), An. evansae (1.7%), An. brasiliensis (0.6%), An. intermedius (0.3%), An. mediopunctatus (0.5%), An. periassui (0.08%) and An. argyritarsis (0.04%). The highest mosquitoes' population density was observed in May and the lowest one was observed in February and November. These results demonstrate the existence of a high diversity of anophelines in the study areas, showing that anthropic changes in the environment and climate variability affect both the population density and relative abundance of these vectors.

Determination of total accumulated rainfall, global radiation, evapotranspiration and degree-days originated from the ECMWF model to sugar cane crop

The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.