914 resultados para global solar radiation
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The surface solar radiation (SSR) is of great importance to bio-chemical cycle and life activities. However, it is impossible to observe SSR directly over large areas especially for rugged surfaces such as the Qinghai-Tibet Plateau. This paper presented an improved parameterized model for predicting all-sky global solar radiation on rugged surfaces using Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric products and Digital Elevation Model (DEM). The global solar radiation was validated using 11 observations within the plateau. The correlation coefficients of daily data vary between 0.67-0.86, while those of the averages of 10-day data are between 0.79-0.97. The model indicates that the attenuation of SSR is mainly caused by cloud under cloudy sky, and terrain is an important factor influencing SSR over rugged surfaces under clear sky. A positive relationship can also be inferred between the SSR and slope. Compared with horizontal surfaces, the south-facing slope receives more radiation, followed by the west- and east-facing slopes with less SSR, and the SSR of the north-facing slope is the least.
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The relationships between the four radiant fluxes are analyzed based on a 4 year data archive of hourly and daily global ultraviolet (I(UV)), photosynthetically active-PAR (I(PAR)), near infrared (I(NIR)) and broadband global solar radiation (I(G)) collected at Botucatu, Brazil. These data are used to establish both the fractions of spectral components to global solar radiation and the proposed linear regression models. Verification results indicated that the proposed regression models predict accurately the spectral radiant fluxes at least for the Brazilian environment. Finally, results obtained in this analysis agreed well with most published results in the literature. (c) 2010 Elsevier Ltd. All rights reserved.
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In this analysis, using available hourly and daily radiometric data performed at Botucatu, Brazil, several empirical models relating ultraviolet (UV), photosynthetically active (PAR) and near infrared (NIR) solar global components with solar global radiation (G) are established. These models are developed and discussed through clearness index K(T) (ratio of the global-to-extraterrestrial solar radiation). Results obtained reveal that the proposed empirical models predict hourly and daily values accurately. Finally. the overall analysis carried Out demonstrates that the sky conditions are more important in developing correlation models between the UV component and the global solar radiation. The linear regression models derived to estimate PAR and NIR components may be obtained without sky condition considerations within a maximum variation of 8%. In the case of UV, not taking into consideration the sky condition may cause a discrepancy of up to 18% for hourly values and 15% for daily values. (C) 2008 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this analysis, using available hourly and daily radiometric data performed at Botucatu, Brazil, several empirical models relating ultraviolet (UV), photosynthetically active (PAR) and near infrared (NIR) solar global components with solar global radiation (G) are established. These models are developed and discussed through clearness index K(T) (ratio of the global-to-extraterrestrial solar radiation). Results obtained reveal that the proposed empirical models predict hourly and daily values accurately. Finally. the overall analysis carried Out demonstrates that the sky conditions are more important in developing correlation models between the UV component and the global solar radiation. The linear regression models derived to estimate PAR and NIR components may be obtained without sky condition considerations within a maximum variation of 8%. In the case of UV, not taking into consideration the sky condition may cause a discrepancy of up to 18% for hourly values and 15% for daily values. (C) 2008 Elsevier Ltd. All rights reserved.
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Solar radiation is the most important source of renewable energy in the planet; it's important to solar engineers, designers and architects, and it's also fundamental for efficiently determining irrigation water needs and potential yield of crops, among others. Complete and accurate solar radiation data at a specific region are indispensable. For locations where measured values are not available, several models have been developed to estimate solar radiation. The objective of this paper was to calibrate, validate and compare five representative models to predict global solar radiation, adjusting the empirical coefficients to increase the local applicability and to develop a linear model. All models were based on easily available meteorological variables, without sunshine hours as input, and were used to estimate the daily solar radiation at Cañada de Luque (Córdoba, Argentina). As validation, measured and estimated solar radiation data were analyzed using several statistic coefficients. The results showed that all the analyzed models were robust and accurate (R2 and RMSE values between 0.87 to 0.89 and 2.05 to 2.14, respectively), so global radiation can be estimated properly with easily available meteorological variables when only temperature data are available. Hargreaves-Samani, Allen and Bristow-Campbell models could be used with typical values to estimate solar radiation while Samani and Almorox models should be applied with calibrated coefficients. Although a new linear model presented the smallest R2 value (R2 = 0.87), it could be considered useful for its easy application. The daily global solar radiation values produced for these models can be used to estimate missing daily values, when only temperature data are available, and in hydrologic or agricultural applications.
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A climate study of the incidence of downward surface global solar radiation (SSRD) in the Iberian Peninsula (IP) based primarily on ERA-40 reanalysis is presented. NCEP/NCAR reanalysis and ground-based records from several Portuguese and Spanish stations have been also considered. The results showthat reanalysis can capture a similar inter-annual variability as compared to ground-based observations, especially on a monthly basis, even though annual ERA-40 (NCEP/NCAR) values tend to underestimate (overestimate) the observations with a mean relative difference of around 20Wm–2 (40Wm–2). On the other hand, ground-based measurements in Portuguese stations during the period 1964–1989 show a tendency to decrease until the mid-1970s followed by an increase up to the end of the study period, in line with the dimming/brightening phenomenon reported in the literature. Nevertheless, there are different temporal behaviours as a greater increase since the 1970s is observed in the south and less industrialized regions. Similarly, the ERA-40 reanalysis shows a noticeable decrease until the early 1970s followed by a slight increase up to the end of the 1990s, suggesting a dimming/brightening transition around the early 1970s, earlier in the south and centre and later in the north of the IP. Although there are slight differences in the magnitude of the trends as well as the turning year of the dimming/brightening periods, the decadal changes of ERA-40 fairly agree with the ground-based observations in Portugal and Spain, in contrast to most of the literature for other regions of the world, and is used in the climatology of the SSRD in the study area. NCEP/NCAR reanalysis does not capture the decadal variations of SSRD in the IP. The results show that part of the decadal variability of the global radiation in the IP is related to changes in cloud cover (represented in ERA-40).
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dIn this work, a perceptron neural-network technique is applied to estimate hourly values of the diffuse solar-radiation at the surface in São Paulo City, Brazil, using as input the global solar-radiation and other meteorological parameters measured from 1998 to 2001. The neural-network verification was performed using the hourly measurements of diffuse solar-radiation obtained during the year 2002. The neural network was developed based on both feature determination and pattern selection techniques. It was found that the inclusion of the atmospheric long-wave radiation as input improves the neural-network performance. on the other hand traditional meteorological parameters, like air temperature and atmospheric pressure, are not as important as long-wave radiation which acts as a surrogate for cloud-cover information on the regional scale. An objective evaluation has shown that the diffuse solar-radiation is better reproduced by neural network synthetic series than by a correlation model. (C) 2004 Elsevier Ltd. All rights reserved.
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Seasonal variations in the diurnal evolution of the global, diffuse and direct solar radiation at the surface, the clearness index, diffuse fraction and direct fraction are described in detail for the City of Sao Paulo, Brazil. The description is based on measurements of global and diffuse solar radiation carried out over 5.25 years. The diffuse component was measured with a shadow-band device. The annual evolution of the amplitude of the diurnal cycle of all radiometric parameters indicates a seasonal pattern with two distinct periods: autumn-winter and spring-summer. About 10% of the observed period was characterized by clear sky days. This seasonal variation is determined by a larger incidence of clear sky days in the autumn-winter period. Reductions of up to 10% in hourly and daily values of global radiation were observed in conjunction with an increase in particulate matter concentration on clear sky days. The pollution effect may be responsible for the discrepancy, of 16%, found between local and more regional estimates of global solar radiation in Sao Paulo. The diurnal evolution of hourly values of monthly-averaged global and diffuse solar radiation were successfully estimated by the empirical expressions derived here. Daily values of monthly-averaged global solar radiation were satisfactorily estimated using the Angstrom expression.
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Mode of access: Internet.
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A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.
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Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric Research to investigate the global hydrological implications of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2, global mean radiative forcing is larger when aerosol concentration is maximum at the poles leading to a warmer global mean climate and consequently an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature and 3% in precipitation changes by varying the distribution pattern in our simulations: this range is about 50% of the climate change from a doubling of CO2. Hence, our study demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is an idealized study and thus not all important realistic climate processes are modeled.
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The climatic effects of Solar Radiation Management (SRM) geoengineering have been often modeled by simply reducing the solar constant. This is most likely valid only for space sunshades and not for atmosphere and surface based SRM methods. In this study, a global climate model is used to evaluate the differences in the climate response to SRM by uniform solar constant reduction and stratospheric aerosols. Our analysis shows that when global mean warming from a doubling of CO2 is nearly cancelled by both these methods, they are similar when important surface and tropospheric climate variables are considered. However, a difference of 1 K in the global mean stratospheric (61-9.8 hPa) temperature is simulated between the two SRM methods. Further, while the global mean surface diffuse radiation increases by similar to 23 % and direct radiation decreases by about 9 % in the case of sulphate aerosol SRM method, both direct and diffuse radiation decrease by similar fractional amounts (similar to 1.0 %) when solar constant is reduced. When CO2 fertilization effects from elevated CO2 concentration levels are removed, the contribution from shaded leaves to gross primary productivity (GPP) increases by 1.8 % in aerosol SRM because of increased diffuse light. However, this increase is almost offset by a 15.2 % decline in sunlit contribution due to reduced direct light. Overall both the SRM simulations show similar decrease in GPP (similar to 8 %) and net primary productivity (similar to 3 %). Based on our results we conclude that the climate states produced by a reduction in solar constant and addition of aerosols into the stratosphere can be considered almost similar except for two important aspects: stratospheric temperature change and the consequent implications for the dynamics and the chemistry of the stratosphere and the partitioning of direct versus diffuse radiation reaching the surface. Further, the likely dependence of global hydrological cycle response on aerosol particle size and the latitudinal and height distribution of aerosols is discussed.
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By how much does changing radiation from the Sun influence Earth's climate compared with other natural and anthropogenic processes? Answering this question is necessary for making policy regarding anthropogenic global change, which must be detected against natural climate variability. Current knowledge of the amplitudes and time scales of solar radiative output variability available from contemporary solar monitoring and historical reconstructions can help specify climate forcing by changing radiation over multiple time scales.