Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

Estimating hourly net radiation for leaf wetness duration using the Penman-Monteith equation

Leaf wetness duration (LWD) is related to plant disease occurrence and is therefore a key parameter in agrometeorology. As LWD is seldom measured at standard weather stations, it must be estimated in order to ensure the effectiveness of warning systems and the scheduling of chemical disease control. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results for operational use. However, the requirement of net radiation (Rn) is a disadvantage foroperational physical models, since this variable is usually not measured over crops or even at standard weather stations. With the objective of proposing a solution for this problem, this study has evaluated the ability of four models to estimate hourly Rn and their impact on LWD estimates using a Penman-Monteith approach. A field experiment was carried out in Elora, Ontario, Canada, with measurements of LWD, Rn and other meteorological variables over mowed turfgrass for a 58 day period during the growing season of 2003. Four models for estimating hourly Rn based on different combinations of incoming solar radiation (Rg), airtemperature (T), relative humidity (RH), cloud cover (CC) and cloud height (CH), were evaluated. Measured and estimated hourly Rn values were applied in a Penman-Monteith model to estimate LWD. Correlating measured and estimated Rn, we observed that all models performed well in terms of estimating hourly Rn. However, when cloud data were used the models overestimated positive Rn and underestimated negative Rn. When only Rg and T were used to estimate hourly Rn, the model underestimated positive Rn and no tendency was observed for negative Rn. The best performance was obtained with Model I, which presented, in general, the smallest mean absolute error (MAE) and the highest C-index. When measured LWD was compared to the Penman-Monteith LWD, calculated with measured and estimated Rn, few differences were observed. Both precision and accuracy were high, with the slopes of the relationships ranging from 0.96 to 1.02 and R-2 from 0.85 to 0.92, resulting in C-indices between 0.87 and 0.93. The LWD mean absolute errors associated with Rn estimates were between 1.0 and 1.5h, which is sufficient for use in plant disease management schemes.

Biomonitoring genotoxic risks under the urban weather conditions and polluted atmosphere in Santo Andre, SP, Brazil, through Trad-MCN bioassay

The present study was made to check if the Trad-MCN bioassay, developed with inflorescences of Tradescantia pallida cv. Purpurea, might discriminate genotoxic risks in areas of the city of Santo Andre (SE Brazil) contaminated by different air pollutants, and periods of the year when risks are higher, and to determine if the variations in the frequency of micronuclei (MCN) can be explained by environmental factors that characterize the stressful situation in each site. Potted plants were exposed in sites highly contaminated by ozone (Capuava and School) and in sites reached by high vehicular emissions (downtown and Celso Daniel Park). Pedroso Park, far from the polluted areas, was taken as reference. From September 2003 to September 2004, 20 young inflorescences were collected twice a week from each place and the frequencies of MCN were estimated. The environmental conditions observed in the polluted sites were stressful enough to promote an increase of MCN, mainly in sites reached by high vehicular emissions. But MCN rates in Capuava and at Celso Daniel Park could not be predicted only by pollutants which characterized the air contamination in these sites. More severe weather conditions, mainly low temperature, relative humidity and rainfall, caused an increase of MCN. Improvement of the biomonitoring system is recommended to minimize this negative influence of weather factors. (C) 2008 Elsevier Inc. All rights reserved.

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

Weather conditions and moon phase influence on Tropical Screech Owl and Burrowing Owl detection by playback

Sampling owls in a reliable and standardized way is not easy given their nocturnal habits. Playback is a widely employed technique to survey owls. We assessed the influence of wind speed, temperature, air humidity, and moon phase on the response rate of the Tropical Screech Owl Megascops choliba and the Burrowing Owl Athene cunicularia in southeast Brazil. Tropical Screech Owl occurs in scrubland and wooded habitats, whereas the Burrowing Owl inhabits open grasslands to grassland savannah. Sixteen survey points were systematically distributed in four different landscape types, ranging from open grassland to woodland savannah. Field work was conducted in 2004 from June to December, the reproductive season of the two owl species. Our study design consisted of eight field expeditions of five nights each; four expeditions occurred under full moon and four under new moon conditions. At each survey station, we performed a broadcast/listening sequence involving several calls and vocalizations from each species, starting with Tropical Screech Owl (the smaller species). From 112 sample periods for each species within their respective preferred habitats, we obtained 54 responses from Tropical Screech Owl (48% response rate) and 30 responses (27% response rate) from Burrowing Owl. We found that the response rate of Tropical Screech Owl increased under conditions of higher temperature and air humidity, while the response rate of Burrowing Owl was higher during full moon nights.