A technique for mapping global illuminance from satellite data

A technique for mapping global illuminance from satellite data was developed. A five-year (1998–2002) climatology of global solar illuminance obtained from this technique is presented for Thailand using hourly GMS-5 satellite data. The technique is based on a radiation budget model which traces solar radiation as it is scattered, absorbed and reflected back to space. The model produces an earth-atmospheric albedo in the satellite spectral window as well as global illuminance at the earth’s surface. The model is tuned using surface illuminance measurements at four stations in Thailand: Chiang Mai (18.78°N, 98.98°E), Ubon Ratchatani (15.25°N, 104.87°E), Songkhla (7.20°N, 100.60 °E) and Nakhon Pathom (13.82°N, 100.04°E). In the mapping process, a satellite earth-atmospheric albedo at any locations yields a cloud-atmospheric albedo in the satellite band, which is then transformed into a cloud-atmospheric albedo in the photopic band. Having obtained the photopic cloud-atmospheric albedo, the model calculates surface illuminance. The model gives a root mean square difference of 8.1% and a mean bias difference of −2.6% when tested against an independent data set. Monthly average maps are presented covering Thailand for local times of 10:30, 12:30 and 14:30.     

Estimation of solar radiation over Cambodia from long-term satellite data

In this work, monthly average daily global solar irradiation over Cambodia was estimated from a long-term satellite data. A 14-year period (1995–2008) of visible channel data from GMS5, GOES9 and MTSAT-1R satellites were used to provide earth-atmospheric reflectivity. A satellite-based solar radiation model developed for a tropical environment was used to estimate surface solar radiation. The model relates the satellite-derived earth-atmospheric reflectivity to absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation due to water vapour was calculated from precipitable water derived from ambient relative humidity and temperature. Ozone data from the TOMS and OMI satellite data were employed to compute the solar radiation absorption by ozone. The depletion of radiation due to aerosols was estimated from the visibility data. Five new solar radiation measuring stations were established at Cambodian cities, namely Siem Reap (13.87°N, 103.85°E), Kompong Thom (12.68°N, 104.88°E), Phnom Penh (11.55°N, 104.83°E), Sihanouke Ville (10.67°N, 103.63°E) and Kampot (10.70°N, 104.28°E). Global solar radiation measured at these stations was used to validate the model. The validation was also carried out by using solar radiation measured at four Thai meteorological stations. These stations are situated near the Cambodian border. Monthly average daily global irradiation from these stations was compared with that calculated from the model. The measured and calculated irradiation is in good agreement, with the root mean square difference of 6.3%, with respect to the mean values. After the validation, the model was used to calculate monthly average daily global solar irradiation over Cambodia. Based on this satellite-derived irradiation, solar radiation maps for Cambodia were generated. These maps show that solar radiation climate of this country is strongly influenced by the monsoons. A solar radiation database was also generated for solar energy applications in Cambodia.     

Satellite-derived solar resource maps for Myanmar

Solar resource maps for use in solar energy applications have been produced for Myanmar. A satellite-based solar radiation model, originally developed for the tropics, was improved and applied for the region. A 13-year period (1998–2010) of imagery data from GMS 5, GOES 9 and MTSAT-1R satellites was used as the main input in the model. The absorption and scattering of solar radiation by various atmospheric constituents was also taken into account. The absorption of solar radiation due to water vapour was estimated from precipitable water database obtained from the National Center for Environmental Protection (NCEP), USA. The total column ozone obtained from TOMS/EP and OMI/AURA satellites were used to calculate solar radiation absorption by ozone. The visibility data observed at meteorological stations in Myanmar and neighbouring countries were employed to estimate solar radiation depletion due to aerosols. In order to validate the model, five pyranometer stations were established in different regions of Myanmar and a two-year period of data from these stations were used for the model validation. Additionally, global solar radiation measured at 10 stations in a neighbouring country was also employed for the validation. It was found that monthly average global radiation obtained from the measurements and that estimated from the model was in good agreement, with a root mean square difference of 9.6% at monthly scale. After the validation, the model was used to estimate monthly average global radiation over Myanmar and the results were presented as solar resource maps. The maps revealed that geographical distribution of solar radiation was strongly influenced by the topography of the country and the tropical monsoons.     

A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model

This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons.     

A method for estimating direct normal solar irradiation from satellite data for a tropical environment

In order to investigate a potential use of concentrating solar power technologies and select an optimum site for these technologies, it is necessary to obtain information on the geographical distribution of direct normal solar irradiation over an area of interest. In this work, we have developed a method for estimating direct normal irradiation from satellite data for a tropical environment. The method starts with the estimation of global irradiation on a horizontal surface from MTSAT-1R satellite data and other ground-based ancillary data. Then a satellite-based diffuse fraction model was developed and used to estimate the diffuse component of the satellite-derived global irradiation. Based on this estimated global and diffuse irradiation and the solar radiation incident angle, the direct normal irradiation was finally calculated. To evaluate its performance, the method was used to estimate the monthly average hourly direct normal irradiation at seven pyrheliometer stations in Thailand. It was found that values of monthly average hourly direct normal irradiation from the measurements and those estimated from the proposed method are in reasonable agreement, with a root mean square difference of 16% and a mean bias of −1.6%, with respect to mean measured values. After the validation, this method was used to estimate the monthly average hourly direct normal irradiation over Thailand by using MTSAT-1R satellite data for the period from June 2005 to December 2008. Results from the calculation were displayed as hourly and yearly irradiation maps. These maps reveal that the direct normal irradiation in Thailand was strongly affected by the tropical monsoons and local topography of the country.     

Development of a method for generating operational solar radiation maps from satellite data for a tropical environment

Despite a considerable number of publications which use satellite data to map solar radiation, relatively few studies have been undertaken in a tropical environment. In this study, we have developed a method to produce operational solar radiation maps from satellite data for this environment. The method is based on a physical model which relates the satellite-derived earth–atmospheric reflectivity from visible channel of GMS-4 and GMS-5 to the transmissivity of the atmosphere. Cloud reflectivity was determined from satellite data, while radiation absorbed by water vapour, ozone and aerosols and radiation scattered by aerosols were determined from ground-based meteorological data. Techniques for determining the radiation depleted by these atmospheric constituents over a whole country were also presented. Satellite data of a six-year period (1993–1998) with approximately ten thousand satellite images were used to construct the maps. When tested against an independent data set, monthly average of daily global irradiation calculated from this method agree with that obtained from the measurements with the relative root mean square difference of 6.8% with respect to the mean values. Solar radiation is presented as twelve maps showing the monthly average of global irradiation and one map showing the yearly average of global irradiation. Radiation patterns from the maps show a strong influence of the tropical monsoons.     

Generation of operational maps of global solar irradiation on horizontal plan and of direct normal irradiation from Meteosat imagery by using SOLARMET

The physical model SOLARMET, elaborated in ENEA (Italian National Agency for New Technologies, Energy and Environment), provides hourly average global solar irradiance on a horizontal surface (GHi) and hourly average direct normal solar irradiance (DNi) for Italy based on primary satellite images in the visible band.

In the present study, the hourly estimates of surface radiation generated by SOLARMET have been summed up to produce monthly average daily irradiation maps. Hourly and monthly maps were done for the years 1996 and 2002. The parameters of this model were obtained by comparing the Meteosat satellite data with ground data gathered in 2002. Differences, relative to 1996, between SOLARMET estimates and observations obtained over two radiation networks of Italian ground sites are presented: the Meteorological Service of the Italian Air Force and National Agro-Meteorological Network; In total 51 ground stations. The comparison between SOLARMET and the previous Italian method carried out in ENEA shows an improvement due to SOLARMET. Such comparison between the values derived using SOLARMET and previous ENEA methodologies and with data from ground-based stations was possible only for monthly averages of daily global radiation due to an almost total lack of direct radiation ground data in Italy.

The operational monthly solar radiation maps, showing solar energy potentials, permit the selection of construction sites to solar energy project developers. In Italy, these data are necessary for installing solar thermal concentration power plants in support of the R&S program recently funded to demonstrate the possibility of these technologies.     

METSTAT—The solar radiation model used in the production of the National Solar Radiation Data Base (NSRDB)

This paper describes selectee aspects of the METSTAT (Meteorological/Statistical) solar radiation model. METSTAT was developed specifically to support the production of the National Solar Radiation Data Base for the United States. The model was used to estimate hourly values of direct normal, diffuse horizontal, and global horizontal solar radiation for those times and locations for which measured data were not available. The input parameters for METSTAT include total and opaque cloud cover, aerosol optical depth, precipitable water vapor, ozone, surface albedo, snow depth, days-since-last-snowfall, atmospheric pressure and present weather. The model employs deterministic algorithms to generate accurate monthly means for each element for each hour and statistical algorithms to simulate the statistical and stochastic characteristics of multiyear solar radiation data sets.     

Techniques for the precise estimation of hourly values of global, diffuse and direct solar radiation

The method usually used to compute solar radiation, when no measured data are available, is the well-known regression technique relating mean daily totals of global and diffuse solar radiation with the mean duration of sunshine. Using this method and taking into account the first order multiple reflections between the ground and the atmosphere, regression parameters were obtained from the monthly mean values of daily totals of global solar radiation and sunshine at a network of 16 stations in India. Daily values of global and diffuse solar radiation were then computed for 121 stations, where sunshine data are available for periods of 6–28 yr, using interpolated values of the regression parameters. Where no sunshine data were available, global and diffuse solar radiation were computed from cloud observations, using the inverse relationship between sunshine and cloudiness. Further, using the empirical relationship between daily totals and the corresponding hourly values of global and diffuse solar radiation, two sets of curves were prepared valid for the whole country, using which mean hourly values of global and diffuse radiation could be deduced from the corresponding daily totals, with a high degree of accuracy. The paper discusses the validity of the techniques used for computing daily and hourly values of global and diffuse solar radiation from sunshine and cloud amounts at an extended network of 145 stations in India and stresses the fact that such techniques are successful, only if accurate data on both radiation and sunshine are available at a widely distributed network of stations for a minimum period from at least 5 to 6 yr, using carefully calibrated and well-maintained instruments of the required quality. Theoretical models have also been used to compute clear sky noon values of global, diffuse and direct solar radiation from the solar constant, allowing for attenuation by atmospheric constituents such as ozone, water vapour, dust and aerosols. Using a simple model, calculations of global and diffuse solar radiation on clear days were made for 145 stations from values of the solar constant and measured values of ozone, water vapour and atmospheric turbidity. A method of extending the technique to overcast skies and partly clouded skies is discussed. The values of the mean annual transmission factor for global solar radiation under cloud-free conditions using the two methods show excellent agreement and establishes the soundness of the regression technique on one hand and the reliability of the theoretical model used for computing clear sky radiation, on the other.     

Direct beam and hemispherical terrestrial solar spectral distributions derived from broadband hourly solar radiation data

Multiple junction and thin film photovoltaic (PV) technologies respond differently to varying terrestrial spectral distributions of solar energy. PV device and system designers are concerned with the impact of spectral variation on PV specific technologies. Spectral distribution data are generally very rare, expensive, and difficult to obtain. We modified an existing empirical spectral conversion model to convert hourly broadband global (total hemispherical) horizontal and direct normal solar radiation to representative spectral distributions. Hourly average total hemispherical and direct normal beam solar radiation, such as provided in Typical Meteorological Year (TMY) data, are spectral model input data. Default or prescribed atmospheric aerosols and water vapor are possible inputs. Individual hourly and monthly and annual average spectral distributions are computed for a specified tilted surface. The spectral range is from 300 nm to 1800 nm. The model is a modified version of the Nann and Riordan SEDES2 model. Measured hemispherical spectral distributions for a wide variety of conditions at the Solar Radiation Research Laboratory at the National Renewable Energy Laboratory, Golden, Co. and Florida Solar Energy Center (Cocoa, FL) show that reasonable spectral accuracy of about ±10% is obtainable with exceptions for weather events such as snow. Differing cloud climatology and variable albedo and aerosol optical depth atmospheric conditions can lead to spectral model differences of 30–40%.     

Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics

This paper presents semi-empirical models for estimating global and direct normal solar irradiances under clear sky conditions in the tropics. The models are based on a one-year period of clear sky global and direct normal irradiances data collected at three solar radiation monitoring stations in Thailand: Chiang Mai (18.78°N, 98.98°E) located in the North of the country, Nakhon Pathom (13.82°N, 100.04°E) in the Centre and Songkhla (7.20°N, 100.60°E) in the South. The models describe global and direct normal irradiances as functions of the Angstrom turbidity coefficient, the Angstrom wavelength exponent, precipitable water and total column ozone. The data of Angstrom turbidity coefficient, wavelength exponent and precipitable water were obtained from AERONET sunphotometers, and column ozone was retrieved from the OMI/AURA satellite. Model validation was accomplished using data from these three stations for the data periods which were not included in the model formulation. The models were also validated against an independent data set collected at Ubon Ratchathani (15.25°N, 104.87°E) in the Northeast. The global and direct normal irradiances calculated from the models and those obtained from measurements are in good agreement, with the root mean square difference (RMSD) of 7.5% for both global and direct normal irradiances. The performance of the models was also compared with that of other models. The performance of the models compared favorably with that of empirical models. Additionally, the accuracy of irradiances predicted from the proposed model are comparable with that obtained from some rigorous physical models.     

Solar radiation models—A review

Solar radiation models for predicting the average daily and hourly global radiation, beam radiation and diffuse radiation on horizontal surface are reviewed in this article. Estimations of monthly average hourly global radiation from daily summations are discussed. It was observed that Collares‐Pereira and Rabl model as modified by Gueymard (CPRG) yielded the best performance for estimating mean hourly global radiation incident on a horizontal surface for Indian regions. Estimations of monthly average hourly beam and diffuse radiation are discussed. It was observed that Singh‐Tiwari and Jamil‐Tiwari both models generally give better results for climatic conditions of Indian regions. Therefore, their use is recommended for composite climate of Indian regions. Empirical correlations developed to establish a relationship between the hourly diffuse fraction and the hourly clearness index using hourly global and diffuse irradiation measurements on a horizontal surface are discussed. Fifty models using the Angstrom–Prescott equation to predict the average daily global radiation with hours of sunshine are considered. It was reported that Ertekin and Yaldiz model showed the best performance against measured data of Konya, Turkey. Copyright © 2010 John Wiley & Sons, Ltd.     

Modeling the luminous efficacy of direct and diffuse solar radiation using information on cloud,aerosol and water vapor in the tropics

This paper presents luminous efficacy models for direct and diffuse solar irradiance using information on cloud, aerosol and water vapor in the tropics. The model is based on five years (2007–2011) of diffuse illuminance and irradiance measurements and two years of direct illuminance and irradiance measurements, April 2010–March 2012. Data are taken at four solar radiation monitoring stations in Thailand, specifically Chiang Mai (18.78 °N, 98.98 °E) in the Northern region, Ubon Ratchathani (15.25 °N, 104.87 °E) in the Northeastern region, Nakhon Pathom (13.82 °N, 100.04 °E) in the Central region and Songkhla (7.20 °N, 100.60 °E) in the Southern region. The models express luminous efficacy as functions of the aerosol optical depth and precipitable water, obtained from the AERONET network, and a cloud index for hourly time scales derived from the MTSAT-1R satellite. The model performance is good when validated against independent data from these stations. Root mean square differences (RMSD) of 9.7% and 6.8% for direct normal efficacy and diffuse efficacy, respectively are obtained. The models compared favorably with most existing models when tested against these independent data.     

A comparison of estimated and measured values of solar radiation in Elazi , Turkey

In this study, variation of global solar radiation reaching the Elazi region at hourly and monthly average daily periods was examined measuring daily global solar radiation between April 1994 and March 1995 by a Kipp–Zonen pyranometer. Taking the measured values as reference, the statistical performance of the three equations used in estimating the monthly average global solar radiation was investigated. Secondly, it was shown that ‘bright sunshine hours/daylength’ and its standard derivation could be used to estimate the monthly daily ‘solar radiation/extraterrestrial radiation’ by applying the maximum likelihood quadratic fit method to the data taken from the state Meteorological Office in Elazi between 1983–1994.     

Assessment of diffuse solar energy under general sky condition using artificial neural network

In this paper, artificial neural network (ANN) models are developed for estimating monthly mean hourly and daily diffuse solar radiation. Solar radiation data from 10 Indian stations, having different climatic conditions, all over India have been used for training and testing the ANN model. The coefficient of determination (R²) for all the stations are higher than 0.85, indicating strong correlation between diffuse solar radiation and selected input parameters. The feedforward back-propagation algorithm is used in this analysis. Results of ANN models have been compared with the measured data on the basis of percentage root-mean-square error (RMSE) and mean bias error (MBE). It is found that maximum value of RMSE in ANN model is 8.8% (Vishakhapatnam, September) in the prediction of hourly diffuse solar radiation. However, for other stations same error is less than 5.1%. The computation of monthly mean daily diffuse solar radiation is also carried out and the results so obtained have been compared with those of other empirical models. The ANN model shows the maximum RMSE of 4.5% for daily diffuse radiation, while for other empirical models the same error is 37.4%. This shows that ANN model is more accurate and versatile as compared to other models to predict hourly and daily diffuse solar radiation.     

Generation of synthetic daily global solar radiation data based on ERA-Interim reanalysis and artificial neural networks

Four variables (total cloud cover, skin temperature, total column water vapour and total column ozone) from meteorological reanalysis were used to generate synthetic daily global solar radiation via artificial neural network (ANN) techniques. The goal of our study was to predict solar radiation values in locations without ground measurements, by using the reanalysis data as an alternative to the use of satellite imagery. The model was validated in Andalusia (Spain), using measured data for nine years from 83 ground stations spread over the region. The geographical location (latitude, longitude), the day of the year, the daily clear sky global radiation, and the four meteorological variables were used as input data, while the daily global solar radiation was the only output of the ANN. Sixty five ground stations were used as training dataset and eighteen stations as independent dataset. The optimum network architecture yielded a root mean square error of 16.4% and a correlation coefficient of 94% for the testing stations. Furthermore, we have successfully tested the forecasting capability of the model with measured radiation values at a later time. These results demonstrate the generalization capability of this approach over unseen data and its ability to produce accurate estimates and forecasts.     

Solar energy distribution over Egypt using cloudiness from Meteosat photos

In Egypt, there are 10 ground stations for measuring the global solar radiation, and five stations for measuring the diffuse solar radiation. Every day at noon, the Meteorological Authority in Cairo receives three photographs of cloudiness over Egypt from the Meteosat satellite, one in the visible, and two in the infra-red bands (10.5–12.5 μm) and (5.7–7.1 μm). The monthly average cloudiness for 24 sites over Egypt are measured and calculated from Meteosat observations during the period 1985–1986.

Correlation analysis between the cloudiness observed by Meteosat and global solar radiation measured from the ground stations is carried out. It is found that, the correlation coefficients are about 0.90 for the simple linear regression, and increase for the second and third degree regressions. Also, the correlation coefficients for the cloudiness with the diffuse solar radiation are about 0.80 for the simple linear regression, and increase for the second and third degree regression. Models and empirical relations for estimating the global and diffuse solar radiation from Meteosat cloudiness data over Egypt are deduced and tested. Seasonal maps for the global and diffuse radiation over Egypt are carried out.     

基于线性方法的内蒙古地区太阳总辐射月均值估算

探讨了内蒙古地区太阳总辐射月均值与日照百分率的关系,基于5个气象站1996—1998年连续3 a的月日照时数（n）和太阳总辐射值（R_s）。计算得到Angstrom方程的系数a和b,与和清华等拟合得到的中国西部太阳总辐射公式中的a=0.185,b=0.595,比较一致。同时,R_s和n之间的直接线性关系,R与月平均温度（T）之间的直接线性关系也能用来估算太阳总辐射月均值,总均方根误差约为80 MJ·m^-2/month,总百分比误差约为18%。     

Monthly mean hourly global solar radiation estimation

In this paper, selected empirical models were used to estimate the monthly mean hourly global solar radiation from the daily global radiation at three sites in the east coast of Malaysia. The purpose is to determine the most accurate model to be used for estimating the monthly mean hourly global solar radiation in these sites. The hourly global solar radiation data used for the validation of selected models were obtained from the Malaysian Meteorology Department and University Malaysia Terengganu Renewable Energy Station. In order to indicate the performance of the models, the statistical test methods of the normalized mean bias error, normalized root mean square error, correlation coefficient and t-statistical test were used. The monthly mean hourly global solar radiation values were calculated by using six models and the results were compared with corresponding measured data. All the models fit the data adequately and can be used to estimate the monthly mean hourly global solar radiation. This study finds that the Collares-Pereira and Rabl model performed better than the other models. Therefore the Collares-Pereira and Rabl model is recommended to estimate the monthly mean hourly global radiations for the east coast of Malaysia with humid tropical climate and in elsewhere with similar climatic conditions.     

Global solar radiation estimation from measurements of visibility and air temperature extremes

Solar radiation is the main source of energy for the survival of life and its associated activities. It is important to know accurate solar radiation value in areas such as agricultural activities, solar energy systems, heating, and meteorology. In this study, we present a model for the estimation of solar radiation value with other meteorological parameters in cases where solar radiation cannot be measured or not available. This model is based on the relationship between solar radiation and measured air temperature and visibility extremes. As is known, the incident global solar radiation is attenuated by clouds, aerosols, ozone layer, water vapor, etc.. In the model, the attenuation of the solar radiation is expressed by dew point temperature, visibility, and the maximum and minimum air temperatures. Dew-point temperature refers to the effect of water vapor on solar radiation, air temperature extremes are used to signify cloudiness. Visibility also gives the effect on the attenuation of solar radiation by air pollutants and aerosols in the model. The model was applied to the data taken from meteorological stations in Turkey. Error analysis was performed and compared with the models in the literature and satisfactory results were obtained.

Abbreviations H: Daily total global solar radiation, units of MJ ? m^?2 ? day^?1; H₀: Extraterrestrial solar radiation, units of MJ ? m^?2 ? day^?1; H_m: Measured daily total global solar radiation, units of MJ ? m^?2 ? day^?1; H_c: Calculated daily total global solar radiation, units of MJ ? m^?2 ? day^?1; T_min: Daily minimum temperature, units of °C; T_max: Daily maximum temperature, units of °C; RH: T_dew: Relative humidity, units of %rh; Dew-point temperature, units of °C