Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a...Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a given set of locations and calendar days, analyzing interannual trends in GSR and SD is important to evaluate, predict or regulate the cycles of energy and water between geosphere and atmosphere. This study aimed to exemplify interannual trends in GSR and SD, which had been recorded from 2001 to 2022 in 40 meteorological stations in Japan, and validate the applicability of an SD-based model to the evaluation of GSR. Both the measured GSR and SD had increased in many of the stations in the study period with averaged rates of 0.252 [W·m−2·y−1] and 0.015 [h·d−1·y−1], respectively. The offset and the slope of the SD-based model were estimated by fitting the model to the measured data sets and were found to have been almost constant with the averages of 0.201[-] and 0.566[-], respectively, indicating that characteristics of the SD-GSR relation had not varied for the 22-year period and that the model and its parameter set can be stationarily applicable to the analyses and predictions of GSR in recent years. The stable trends in both parameters also implied that the upward trend in SD can be a main explanatory factor for that in the measured GSR. The upward trend in SD had coincided with the increase in the frequency of heavy-shortened rains, suggesting that the time period of each rainfall event had gradually decreased, which may be attributable to the obtained upward trend in SD. Further studies are required to clarify if there is some cause-effect relation between the changes in rainfall patterns and the standard level of solar radiation reaching the land surface.展开更多
The aim of this study is the determination of a suitable solar radiation model for the twelve cities of Chad based on meteorological data. Three appropriate models are used to estimate the solar radiation of each site...The aim of this study is the determination of a suitable solar radiation model for the twelve cities of Chad based on meteorological data. Three appropriate models are used to estimate the solar radiation of each site. The choice of these models is based on statistical tests such as the Root Mean Square Error (RMSE), the Mean Bias Error (MBE), the Mean Percentage Error (MPE), and the Nash-Sutcliffe Equation (NSE). The obtained results show that the Angstrom-Prescott model is the most suitable for the calculation of global solar radiation in the sites of Bongor, Pala, Am-timan and Mongo. For the sites of Moundou, Sarh and Bokoro the Allen model is the most adapted for the calculation of global solar radiation. On the other hand the Sabbagh model is the most appropriate for the sites of Faya-Largeau, Abeche, N’Djamena, Ati and Moussoro. It has been revealed that Abeche is the site with the highest solar radiation value equal to 6.354 kWh/m2 and Ati is the site where the solar radiation has the lowest value around 5.523 kWh/m2. Based on the obtained results, it is demonstrated that the three climatic zones of Chad have a good solar potential and consequently suitable for the exploitation of the solar energy systems.展开更多
The Angstrom-Prescott formula is commonly used in climatological calculation methods of solar radiation simulation. Fitting the coefficients is carried out using linear regression and in recent years it has been found...The Angstrom-Prescott formula is commonly used in climatological calculation methods of solar radiation simulation. Fitting the coefficients is carried out using linear regression and in recent years it has been found that these coefifcients have obvious spatial variability. A common solution is to divide the study area into several subregions and ift the coefifcients one by one. Here, we use ground observation data for sunshine hours and solar radiation from 1961 to 2010. Adopting extraterrestrial radiation as the initial value, Angstrom-Prescott coefifcients are obtained by Geographically Weighted Regression at a national scale. The surfaces of solar radiation are obtained on the basis of the surfaces of sunshine hours interpolated by high accuracy surface modeling and astronomical radiation;results from spatial y nonstationary and error comparison tests show that Angstrom-Prescott coefifcients have signiifcant spatial nonstationarity. Compared to existing research methods, the method presented here achieves a better simulation effect.展开更多
Angstrom-Prescott equation(AP)is the algorithm recommended by the Food and Agriculture Organization(FAO)of the United Nations for calculating the surface solar radiation(R_(s))to support the estimation of crop evapotr...Angstrom-Prescott equation(AP)is the algorithm recommended by the Food and Agriculture Organization(FAO)of the United Nations for calculating the surface solar radiation(R_(s))to support the estimation of crop evapotranspiration.Thus,the a_(s) and b_(s) coefficients in the AP are vital.This study aims to obtain coefficients a_(s) and b_(s) in the AP,which are optimized for Chinas comprehensive agricultural divisions.The average monthly solar radiation and relative sunshine duration data at 121 stations from 1957-2016 were collected.Using data from 1957 to 2010,we calculated the monthly a_(s) and b_(s) coefficients for each subregion by least-squares regression.Then,taking the observation values of R_(s) from 2011 to 2016 as the true values,we estimated and compared the relative accuracy of R_(s) calculated using the regression values of coefficients a_(s) and b_(s) and that calculated with the FAO recommended coefficients.The monthly coefficients,a_(s) and b_(s),of each subregion are significantly different,both temporally and spatially,from the FAO recommended coefficients.The relative error range(0-54%)of R_(s) calculated via the regression values of the a_(s) and b_(s) coefficients is better than the relative error range(0-77%)of R_(s) calculated using the FAO suggested coefficients.The station-mean relative error was reduced by 1% to 6%.However,the regression values of the a_(s) and b_(s) coefficients performed worse in certain months and agricultural subregions during verification.Therefore,we selected the a_(s) and b_(s) coefficients with the minimum R_(s) estimation error as the final coefficients and constructed a coefficient recommendation table for 36 agricultural production and management subregions in China.These coefficient recommendations enrich the case study of coefficient calibration for the AP in China and can improve the accuracy of calculating R_(s) and crop evapotranspiration based on existing data.展开更多
文摘Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a given set of locations and calendar days, analyzing interannual trends in GSR and SD is important to evaluate, predict or regulate the cycles of energy and water between geosphere and atmosphere. This study aimed to exemplify interannual trends in GSR and SD, which had been recorded from 2001 to 2022 in 40 meteorological stations in Japan, and validate the applicability of an SD-based model to the evaluation of GSR. Both the measured GSR and SD had increased in many of the stations in the study period with averaged rates of 0.252 [W·m−2·y−1] and 0.015 [h·d−1·y−1], respectively. The offset and the slope of the SD-based model were estimated by fitting the model to the measured data sets and were found to have been almost constant with the averages of 0.201[-] and 0.566[-], respectively, indicating that characteristics of the SD-GSR relation had not varied for the 22-year period and that the model and its parameter set can be stationarily applicable to the analyses and predictions of GSR in recent years. The stable trends in both parameters also implied that the upward trend in SD can be a main explanatory factor for that in the measured GSR. The upward trend in SD had coincided with the increase in the frequency of heavy-shortened rains, suggesting that the time period of each rainfall event had gradually decreased, which may be attributable to the obtained upward trend in SD. Further studies are required to clarify if there is some cause-effect relation between the changes in rainfall patterns and the standard level of solar radiation reaching the land surface.
文摘The aim of this study is the determination of a suitable solar radiation model for the twelve cities of Chad based on meteorological data. Three appropriate models are used to estimate the solar radiation of each site. The choice of these models is based on statistical tests such as the Root Mean Square Error (RMSE), the Mean Bias Error (MBE), the Mean Percentage Error (MPE), and the Nash-Sutcliffe Equation (NSE). The obtained results show that the Angstrom-Prescott model is the most suitable for the calculation of global solar radiation in the sites of Bongor, Pala, Am-timan and Mongo. For the sites of Moundou, Sarh and Bokoro the Allen model is the most adapted for the calculation of global solar radiation. On the other hand the Sabbagh model is the most appropriate for the sites of Faya-Largeau, Abeche, N’Djamena, Ati and Moussoro. It has been revealed that Abeche is the site with the highest solar radiation value equal to 6.354 kWh/m2 and Ati is the site where the solar radiation has the lowest value around 5.523 kWh/m2. Based on the obtained results, it is demonstrated that the three climatic zones of Chad have a good solar potential and consequently suitable for the exploitation of the solar energy systems.
基金National Key Technologies R&D Program of China(2013BAC03B05)National High-tech R&D Program of China(2013AA122003)
文摘The Angstrom-Prescott formula is commonly used in climatological calculation methods of solar radiation simulation. Fitting the coefficients is carried out using linear regression and in recent years it has been found that these coefifcients have obvious spatial variability. A common solution is to divide the study area into several subregions and ift the coefifcients one by one. Here, we use ground observation data for sunshine hours and solar radiation from 1961 to 2010. Adopting extraterrestrial radiation as the initial value, Angstrom-Prescott coefifcients are obtained by Geographically Weighted Regression at a national scale. The surfaces of solar radiation are obtained on the basis of the surfaces of sunshine hours interpolated by high accuracy surface modeling and astronomical radiation;results from spatial y nonstationary and error comparison tests show that Angstrom-Prescott coefifcients have signiifcant spatial nonstationarity. Compared to existing research methods, the method presented here achieves a better simulation effect.
基金National High Resolution Earth Observation System(the Civil Part)Technology Projects of ChinaLocal Scientific&Technological Development Projects of Qinghai Guided by Central Government of ChinaDisaster Research Foundation of PICC P&C,No.2017D24-03。
文摘Angstrom-Prescott equation(AP)is the algorithm recommended by the Food and Agriculture Organization(FAO)of the United Nations for calculating the surface solar radiation(R_(s))to support the estimation of crop evapotranspiration.Thus,the a_(s) and b_(s) coefficients in the AP are vital.This study aims to obtain coefficients a_(s) and b_(s) in the AP,which are optimized for Chinas comprehensive agricultural divisions.The average monthly solar radiation and relative sunshine duration data at 121 stations from 1957-2016 were collected.Using data from 1957 to 2010,we calculated the monthly a_(s) and b_(s) coefficients for each subregion by least-squares regression.Then,taking the observation values of R_(s) from 2011 to 2016 as the true values,we estimated and compared the relative accuracy of R_(s) calculated using the regression values of coefficients a_(s) and b_(s) and that calculated with the FAO recommended coefficients.The monthly coefficients,a_(s) and b_(s),of each subregion are significantly different,both temporally and spatially,from the FAO recommended coefficients.The relative error range(0-54%)of R_(s) calculated via the regression values of the a_(s) and b_(s) coefficients is better than the relative error range(0-77%)of R_(s) calculated using the FAO suggested coefficients.The station-mean relative error was reduced by 1% to 6%.However,the regression values of the a_(s) and b_(s) coefficients performed worse in certain months and agricultural subregions during verification.Therefore,we selected the a_(s) and b_(s) coefficients with the minimum R_(s) estimation error as the final coefficients and constructed a coefficient recommendation table for 36 agricultural production and management subregions in China.These coefficient recommendations enrich the case study of coefficient calibration for the AP in China and can improve the accuracy of calculating R_(s) and crop evapotranspiration based on existing data.
