A model for calculating hourly global solar radiation from satellite data in the tropics

A model for calculating global solar radiation from geostationary satellite data is presented. The model is designed to calculate the monthly average hourly global radiation in the tropics with high aerosol load. This model represents a physical relation between the earth-atmospheric albedo derived from GMS5 satellite data and the absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation by water vapour which is important for the tropics, was calculated from ambient temperature and relative humidity. The relationship between the visibility and solar radiation depletion due to aerosols was developed for a high aerosol load environment. This relationship was used to calculate solar radiation depletion by aerosols in the model. The total column ozone from TOMS/EP satellite was employed for the determination of solar radiation absorbed by ozone. Solar radiation from four pyranometer stations was used to formulate the relationship between the satellite band earth-atmospheric albedo and broadband earth-atmospheric albedo required by the model. To test its performance, the model was used to compute the monthly average hourly global radiation at 25 solar radiation monitoring stations in tropical areas in Thailand. It was found that the values of monthly average of hourly global radiations calculated from the model were in good agreement with those obtained from the measurements, with the root mean square difference of 10%. After the validation the model was employed to generate hourly solar radiation maps of Thailand. These maps reveal the diurnal and season variation of solar radiation over the country.     

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.     

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.     

Daily UV radiation modeling with the usage of statistical correlations and artificial neural networks

The information regarding solar UV radiation (UVA + UVB) in Brazil and around the world is scarce with low spatial and temporal coverage. This information scarcity, due to the small number of measuring stations, has directed some researchers towards the creation of computational parametric models or the generation of statistical models for the estimation of the UV radiation from the measurement of the global radiation. Information about UV irradiation is expanded for other places where there is only global radiation data. Thus, two stations were set up, in 2008, one in the city of Pesqueira and the other in Araripina, both in the state of Pernambuco, for simultaneous measurements of daily global solar and UV radiation. Another station is being set up in Recife-PE, completing a group of stations that are located between latitudes 8 and 10° and longitudes 34–38° W, representing the typical climate of the region. The daily values of G global and UV ultraviolet radiation (A + B) striking the horizontal plane in Pesqueira and Araripina during the time period (2008–2010) were measured, analyzed and compared. The collected data enabled the generation of three different statistical models for estimating the daily UV solar radiation from the daily global radiation: a) linear correlation between global and UV radiation (model 1), b) polynomial correction of the average fraction of UV irradiation, 〈F_UV〉 as a function of the transmittance index of global solar irradiation 〈K_T〉 (model 2) and c) the UV atmospheric transmittance index 〈K_TUV〉 is obtained by multiple regression of the air mass 〈m_r〉and 〈K_T〉 (model 3). Besides, they were modeled by two artificial neural networks: a) estimative of the (F_UV), considering the same physical variables of model 2 (model ANN1) and b) estimative of (K_TUV) from the same physical variables of model 3 (model ANN2). The statistical models and the artificial neural networks displayed a good statistical performance with RMSE% inferior to 5% and MBE between ?0.4%–2%. All the models can be used for estimating the UV radiation in places where there is only global irradiation data.     

Analysis of a solarimetric database for Mexico and comparison with the CSR model

An analysis of the solar radiation database from the network of meteorological stations of the Mexican National Weather Service was carried out. The database includes global irradiance measurements from the oldest 136 stations distributed in the Mexican territory. The consistency of data acquisition from the launch of the stations until 2010 was checked, and visual inspection of graphs of daily irradiance data was carried out, for the first three years operation, to ensure quality and reliability of the data. The results indicate that less than half of the stations have an adequate regularity for data records. With a limited number of selected stations that passed the applied quality criteria, evaluation of hourly and daily global irradiations was carried out. These results were compared to satellite derived data for Mexico, based on NREL's CSR model. The results of the comparison show a good agreement between measured and modeled daily global solar irradiation with an average RMSE of 6.6%. Based on the selected stations, a daily irradiation mean of 5.5 kWh/m²/day is estimated for the country.     

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 model for determining the global solar radiation for Makurdi,Nigeria

An empirical model for determining the monthly average daily global solar radiation on a horizontal surface for Makurdi, Nigeria (Latitude 7°7′N and Longitude 8°6′E) was developed using the Angstrom–Page equation. The solar radiation (W/m²), hours of bright sunshine and cloudiness were measured hourly from 0600 H to 1800 H daily for 18 months. The constants ‘a’ and ‘b’ of the Angstrom linear type equation were determined by plotting the clearness index (H/H_o) against the possible sunshine hours (n_s/N) to obtain the line of best fit. The constant ‘a’ was obtained from the intercept of the line on the y-axis while the constant ‘b’ was obtained from the slope of the line. The developed model for determining the global horizontal solar radiation at the location was H = H_o [0.17 + 0.68(n/N)] with a coefficient of correlation of 0.78. The mean bias error and root mean square error that were used to test the performance of the constants were 0.17% and 1.22% respectively. The measured solar radiation was compared with the solar radiation predicted by the model and no significant difference was found between them using F-LSD at P ≤ 0.05.     

Evaluation of the Heliosat-II method using daily irradiation data for four stations in Iran

Efficient use of solar radiation needs detailed knowledge of its spatial and temporal variations. Such information can be achieved using interpolating measured irradiance by ground stations. But more reliable results can be obtained by processing geostationary satellite images. Heliosat is an algorithm which has been developed to estimate global horizontal irradiance at ground level from images taken in the visible band by the Meteosat satellites.The aim of this study was to evaluate the Heliosat-II model by using daily global solar irradiation data measured at the four radiometric stations in Iran as well as Meteosat-5 images which are recorded by a spacecraft over 63°E. Mean RMSD% and MBD% for all stations were 11.7% and 1.9%, respectively. The mean values of intercept, slope and correlation coefficient were 0.82 (kWh m⁻²), 1.05 and 0.93, respectively. Seasonally, the maximum RMSD occurs in autumn (22.1%) and the minimum is experienced in spring (8.4%). This accuracy is a great achievement for producing a high quality solar radiation atlas in a country such as Iran with very sparse radiometric network and frequently unreliable measured irradiation data.     

Solar radiation model

Solar radiation models for predicting the average daily and hourly global radiation, beam radiation and diffuse radiation are reviewed in this paper. Seven models using the Ångström–Prescott equation to predict the average daily global radiation with hours of sunshine are considered. The average daily global radiation for Hong Kong (22.3°N latitude, 114.3°E longitude) is predicted. Estimations of monthly average hourly global radiation are discussed. Two parametric models are reviewed and used to predict the hourly irradiance of Hong Kong. Comparisons among model predictions with measured data are made.     

An investigation of the performance of 14 models for estimating hourly diffuse irradiation on inclined surfaces at tropical sites

The performance of 14 models for estimating hourly diffuse irradiation on inclined surfaces was investigated. In order to obtain solar radiation data for this investigation, equipment for measuring solar radiation on inclined surfaces facing to the north, south, east and the west at different tilted angles to the horizontal surface (30°, 60° and 90°) were constructed and installed at two tropical sites in Thailand, namely Nakhon Pathom (13.82 °N, 100.04 °E) and Ubon Ratchathani (15.25 °N, 104.87 °E). Radiation data encompassing different periods of 1–4 years were used in this work. Diffuse irradiance measurements at different tilted angles were compared with various model algorithms. Results show that the Muneer and Gueymard models have comparable performance in terms of root mean square difference (RMSD) and these models give the lowest RMSD, as compared to that of the other models.     

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.     

Assessment of the method used to construct clearness index maps for the new European Solar Radiation Atlas (ESRA)

We present an assessment of the methods used to construct maps for a new solar radiation atlas for Europe. For this atlas, station data and satellite-derived data are used in an interpolation/merging process to derive maps of the long-term monthly global radiation that cover an area ranging from 30° W to 70° E and from 25° to 75° N. Our focus is on the discussion of the accuracy of the method applied: a co-kriging technique. Special emphasis is put on a discussion as to whether the use of satellite-derived radiation maps with a low spatial resolution brings benefits.     

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.     

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     

Iterative filtering of ground data for qualifying statistical models for solar irradiance estimation from satellite data

A new technique of filtering solar radiation ground data is proposed for generating models for solar irradiance estimation from geostationary satellite data. The filtering processes consists of an iterative way of selecting the training data set to achieve the best model response. Although in this paper the proposed methodology has been used for solar irradiance modeling, it could be applied to any kind of empirical modeling. The iterative filtering method has proven to have fast convergence and to improve successfully the statistical model response, when applied to hourly global irradiance calculation from satellite-derived irradiances for 13 Spanish locations. Individual statistical models for hourly global irradiance were fitted using the Heliosat I method applied to Meteosat images of 13 Spanish stations for the period 1994–1996.     

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.     

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.     

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 radiation estimations over India using Meteosat satellite images

India is endowed with good solar energy resource due to its geographic position in the equatorial Sun Belt of the earth, but its atmosphere can have eventual large presence of aerosols with the subsequent negative feedback to the solar radiation available. Therefore, solar resource assessment studies over India are of high interest for potential solar energy applications. In this work daily estimations of global horizontal and direct normal irradiation are presented for six locations in India covering the years from 2000 till 2007. These computations have been performed with IrSOLaV/CIEMAT method for computing solar radiation components from Meteosat images with a spatial resolution of less than 5 × 5 km. A brief assessment exercise of the model output have been made with ground measurements available from the World Radiation Data Centre database, which consists only of daily sums of global horizontal irradiation. The daily global horizontal irradiation estimated by the model has shown a general positive bias with the ground measurements in the range of 5%, being the root mean square deviation around 12%, excepting for Trivandrum location where there are evidences of higher uncertainty in the ground measurements. In addition, the dynamical behavior of daily global irradiation is quite well reproduced by the model as a consequence of adding to the input the daily turbidity values estimated from MODIS Terra satellite information. Estimations of direct normal irradiation are also exposed but no assessment was made due to the lack of ground measurements. The importance and need of accurate daily aerosol data with high spatial resolution for solar radiation estimations is pointed out in this work.     

Novel approach in developing hourly global solar radiation model based on peak sunshine hours

The present study explores a novel approach to derive the hourly global solar radiation (HGSR) for any given latitude based on the peak sunshine hours (PSHs). The proposed analytical model describes a relationship between the HGSR and the day length and the PSHs. The applicability of this model is evaluated by comparing the actual and derived values of HGSR for two cities Chennai (13°04′N, 80°17′E) and New Delhi (29°06′N, 77°22′E). To judge the goodness of the proposed model a set of error metrics has been developed by evaluating the variation of actual HGSR from the simulated value for a given day over 12 months. The overall average mean bias error for one year is 1.015% and 1.08% for Chennai and New Delhi, respectively. The agreement between the actual and the simulated values is generally good, with an appreciable correlation of 95%. In particular, unlike the other models this approach requires only two inputs which are easily available for any location. The proposed technique is useful for any solar application designer for deriving the hourly solar radiation values for a given day of any location with less available climate data.