Models to estimate incident solar radiation on Seropédica, Rio de Janeiro

Góis, Givanildo de; Souza, Jessica Cristina Santos; Júnior, José Francisco Oliveira; Delgado, Rafael Coll; Lyra, Guilherme Bastos; Teodoro, Paulo Eduardo

doi:10.14393/bj-v32n2a2016-29877

Cited by 11 publications

(13 citation statements)

References 23 publications

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“…The above corrections for the coefficients did not necessarily result in improved accuracy and precision of H g estimates by the Hargreaves-Samani and Bristow-Campbell methods in other regions [4,15,24], or by considering only one factor climatic conditions (e.g., oceanity/continentality, altitude, air temperature and thermal amplitude) or corrections are valid only for the place where they were proposed. Therefore, the aim of the present study was to fit and to assess the empirical coefficients of the Hargreaves-Samani [12] and Bristow-Campbell [9] methods for the estimation of monthly average daily global solar irradiation in the state of Rio de Janeiro, Brazil, and to propose a simple approach to determine their empirical coefficients in function of the climate.…”

Section: Introductionmentioning

confidence: 96%

“…Solar radiation is a primary source of energy for several physical, chemical and biological processes that occur on Earth, being a factor which conditions air and soil temperature, and the photosynthesis and evapotranspiration processes (ET) [1,2]. Radiation also represents an important meteorological variable in studies of the water needs of irrigated crops, modeling of growth and plant yield, climate changes, in the parameterizations of mesoscale and general circulation models (GCM), among others [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…The method proposed by Hargreaves and Samani [12] stands out for its simplicity and for providing precise and accurate estimates of H g [4,[13][14][15]. It estimates H g based only on air temperature extremes (maximum and minimum) and H o .…”

Section: Introductionmentioning

confidence: 99%

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Assessment of monthly global solar irradiation estimates using air temperature in different climates of the state of Rio de Janeiro, Southeastern Brazil

et al. 2019

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The number of weather stations that measure solar global irradiance (I g ) is scarce, and when it is available, it does not present long-time series, without gaps and high quality. When I g is unavailable, it is possible to estimate its integral over time-solar global irradiation (H g )-using empirical methods. However, for a better performance these methods need to be fitted to the local climatic conditions. The aim of this study was to assess the Hargreaves-Samani (HS) and Bristow-Campbell (BC) methods to estimate monthly average daily H g in the state of Rio de Janeiro, Southeastern Brazil, and to propose a simple approach to determine the empirical coefficients in function of the climate. The methods are based on maximum and minimum air temperature and on extraterrestrial solar irradiation. Series of air temperature extremes and H g from 15 automatic weather stations between 2000 until 2013 were used. The methods were evaluated by the statistical indexes: determination coefficient (r 2 ) of the linear regression between observed and estimated monthly H g , root mean square error (RMSE), Willmott's index (d) and performance index (c). The methods (BC-r 2 > 0.60, d > 0.85 and RMSE < 2.99 MJ m −2 d −1 and HS-r 2 > 0.55, d > 0.75 and RMSE < 3.85 MJ m −2 d −1 ) had satisfactory performance in the estimation of monthly H g for the state of Rio de Janeiro, when their coefficients were fitted to local climatic conditions. The BC presented performance classified as "optimal" (c > 0.85) in approximately 80% of the stations analyzed, while for Hargreaves-Samani, only 55% of the stations were classified as "optimal. " The highest HS coefficients (k r ) occurred in Semiarid (0.246 ± 0,023) and Dry Sub-humid (0.181 ± 0.011) climates and were associated with coastal regions (< 20 km), while the stations in Humid (0.146 ± 0.008), Sub-humid (0.1524 ± 0.003) and Dry Sub-humid (0.162 ± 0.011) climates located in interior regions presented the lowest k r . Thus, it is possible to determine the k r coefficient based only on the climatic classification of the site and distance of the coastal environment. In general, the highest atmospheric transmittance (β 0 -BC method) was observed in Semiarid and Dry Sub-humid climate regions. β 1 and β 2 coefficients did not present a distribution pattern with the local climatology and with the proximity of large water bodies. The methods presented a better performance in Dry Sub-humid and Semiarid climates, due to the lower variability of cloudiness and greater thermal amplitude.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Assessment of monthly global solar irradiation estimates using air temperature in different climates of the state of Rio de Janeiro, Southeastern Brazil

et al. 2019

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“…ere are limitations as to the applicability of Ws since this model does not have fixable coefficients and since estimations for H s can be made only in function of H 0 and ΔT, without proper local calibration [1,5,70]. is result shows the necessity to calibrate the models to the MG climate conditions, similar to that reported in [1,67,68,71] for other locations of Brazil.…”

Section: Resultsmentioning

confidence: 90%

“…We emphasize that the Ws EM had a c-index of 0.01 to 0.29, which is one of the worst fits for all the locations studied. is EM was also not efficient in estimating H s in Cruz das Almas (BA) [5], in North America [70], and in Seropédica (SEB) [71] nor in the different biomes found in the Mato Grosso state, centralwest Brazil [1]. ere are limitations as to the applicability of Ws since this model does not have fixable coefficients and since estimations for H s can be made only in function of H 0 and ΔT, without proper local calibration [1,5,70].…”

Section: Resultsmentioning

confidence: 99%

Global Solar Radiation Models in Minas Gerais, Southeastern Brazil

Monteiro

Martins

2019

Advances in Meteorology

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Accurate and complete global solar radiation (Hs) data at a specific region are crucial for regional climate assessment, crop growth modeling, and all operations that use solar energy. However, in the Minas Gerais state, Southeastern Brazil (SEB), the number of weather stations that measure global solar radiation is scarce, and when it is available, it presents gaps in the time series. An attractive alternative to solve the data gap problem is to estimate global solar radiation using empirical models. In this study, thirteen models based on maximum and minimum air temperatures, precipitation, sunshine duration, and extraterrestrial solar radiation were compared in the daily estimation of Hs. Data from 10 weather stations, from 1999 to 2017, located in Minas Gerais were used. Also, cluster analysis was used to group the localities (weather stations) with similar patterns of model performance, climatic classification (Köppen–Geiger and Thornthwaite), and seasonal data variability, considering minimum and maximum air temperatures, precipitation, sunshine duration, and global solar radiation. Although it is apparently simple, studies on this subject are scarce and the few existing ones in Minas Gerais have flaws, which justifies this study. The models were evaluated by root mean square error (RMSE), mean absolute percentage error (MAPE), mean bias error (BIAS), Willmott’s index of agreement (d), and performance index (c-index). Models based on sunshine duration, such as those proposed by Ertekin and Yaldiz and by Newland, showed the best performance (average c-index = 0.71). Models based on temperature and precipitation showed the worst results (average c-index = 0.41). Cluster analysis showed that there is a similar pattern between the performance of the models, climatic classification, and seasonal variability of data among the localities of Minas Gerais. In general, models that presented extremely poor performance were formed with weather stations located in the dry zone, but with different climate classification, and models that presented very good (and good) performance were composed by weather stations located in the humid zone (dry subhumid) with the same climate classification and similar seasonal variability. Furthermore, the models based on temperature have a tendency to overestimate radiation values below 10 MJ·m−2 day−1 and to underestimate values higher than 25 MJ·m−2 day−1. This point is a limitation of the model for estimating global solar radiation below and above these levels, showing the influence of atmospheric systems and atmospheric attenuation mechanisms of global solar radiation.

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