6 resultados para Wind speed data

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

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The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

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Size-resolved vertical aerosol number fluxes of particles in the diameter range 0.25-2.5 mu m were measured with the eddy covariance method from a 53 m high tower over the Amazon rain forest, 60 km NNW of Manaus, Brazil. This study focuses on data measured during the relatively clean wet season, but a shorter measurement period from the more polluted dry season is used as a comparison. Size-resolved net particle fluxes of the five lowest size bins, representing 0.25-0.45 mu m in diameter, were in general dominated by deposition in more or less all wind sectors in the wet season. This is an indication that the source of primary biogenic aerosol particles may be small in this particle size range. Transfer velocities within this particle size range were observed to increase linearly with increasing friction velocity and increasing particle diameter. In the diameter range 0.5-2.5 mu m, vertical particle fluxes were highly dependent on wind direction. In wind sectors where anthropogenic influence was low, net upward fluxes were observed. However, in wind sectors associated with higher anthropogenic influence, deposition fluxes dominated. The net upward fluxes were interpreted as a result of primary biogenic aerosol emission, but deposition of anthropogenic particles seems to have masked this emission in wind sectors with higher anthropogenic influence. The net emission fluxes were at maximum in the afternoon when the mixed layer is well developed, and were best correlated with horizontal wind speed according to the equation log(10)F = 0.48.U + 2.21 where F is the net emission number flux of 0.5-2.5 mu m particles [m(-2) s(-1)] and U is the horizontal wind speed [ms(-1)] at the top of the tower.

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Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

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Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from X decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yr(-1), but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yr(-1)) is considered in discussion on the use of flux data to validate and interpolate models.

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Brazilian Campos grasslands are rich in species and the maintenance of its diversity and physiognomy is dependent on disturbance (e.g. fire and grazing) Nevertheless, studies about fire intensity and severity are inexistent. The present paper describes fire parameters, using 14 experimental burn plots in southern Brazil (30 degrees 02` to 30 degrees 04`S, and 51 degrees 06` to 51 degrees 09`W. 311masl). Two sites under different fire histories were chosen: frequently burned and excluded since six years. Experimental burning was performed during summer (2006-2007), when most burning takes place in these grasslands. The following parameters were measured: air temperature and moisture, vegetation height, wind speed, fuel (fine, coarse), fuel moisture, fire temperatures (soil level and at 50cm), ash, residuals, flame freight, fire duration: burning efficiency and fire intensity were later calculated. Fuel load varied from 0.39 to 1.44kg.m(-2). and correlated positively with both fire temperature and fire intensity. Fire temperatures ranged 47 to 537.5 degrees C. being higher in the excluded site Fire intensity was low compared to grassland elsewhere (36 5-319.5kW.m(-1)), differing significantly between sties Fine fuel was the variable that best explained fire intensity. The results on fire intensity and severity in Campos grasslands can be considered a pilot study, since plots were very small. However the data provided can help other researchers to get permission for experimentation using larger plots The results provide support for further studies about the effects of fire on grassland vegetation and for studies involving fire models and fire risk prediction