Values Of Global Solar Radiation Research Articles

Evaluation of a grid-connected PV power plant: performance and agrivoltaic aspects

AbstractThe performance ratio, a globally recognized metric that correlates with reported global solar radiation values, serves as a crucial indicator for evaluating the efficiency of grid-connected PV plants. Also, a large scale PV power plant alone can afford some agricultural irrigation energy requirement of a region. In this study, the actual generation data from a power plant located in Bursa province in northwestern Türkiye, during its initial six years of operation have been analyzed. The analysis reveals that the annual electricity production of the power station reaches approximately 10 GWh. Notably, the time period between April and September witnesses a monthly electricity generation exceeding 1 GWh, with September emerging as the most productive month, characterized by an average performance ratio of 94.5% during this six-year period. However, over the span of six years, the highest average electricity generation occurs in July, peaking at 1.34 GWh. Also, the power plant alone can meet the agricultural irrigation energy requirement of the region in the range of 6.7–2.3%. From an environmental impact and global warming perspective, it is noteworthy that during the 36-month period in the summer season, the performance ratio exceeded 100% only three times. However, within the 32-month period in the winter season, the performance ratio exceeded 100% 19 times. This situation indicates that while the reported radiation rates by the managements are consistent with the actual values for the summer months, they need to be revised, especially for the winter months.

THE IMPACT OF ALBEDO, CLOUD COVERS AND GLOBAL SOLAR RADIATION ON GLOBAL WARMING USING UYO COUNTY DATA, NIGERIA

Ways of countering the causes global warming is the world involve all researchers. The impact of albedo, cloud covers and global solar radiation on global warming have been studied using atmospheric data from Uyo. The data was obtained from NIMET. The outcomes were achieved using Microsoft Excel and SPSS packages. The result obtained showed that albedo varies directly with cloud covers and indirectly with the surface temperature and global solar radiation. The mean values of albedo, cloud cover and global solar radiation are 0.5823 (about 58), 72.25 and 15.22358 MJmday. The challenge of low performance of the solar energy systems from April to October is possible. Uyo may be seen as an unvegetated land, devoid of snow according to this research outcome. Making Uyo a fully forested land, global solar radiation would increase, leading to a decrease in cloud cover. This practice would add to the possible way of resolving the challenge of global warming.

Atmospheric water demand constrains net ecosystem production in subtropical mangrove forests

Subtropical mangroves have great potential to sequester atmospheric carbon dioxide (CO2) and thus significantly contribute to climate change mitigation. Meanwhile, the carbon cycling processes in subtropical mangroves are vulnerable to the changing climatic conditions, such as the warming-induced vapor pressure deficit (VPD) increases. However, the impacts of VPD on net ecosystem production (NEP) in subtropical mangroves remain poorly understood due to a lack of detailed assessment of NEP responses to VPD among different mangrove forests over a long-term observational period. In this study, we deployed eddy-covariance systems to measure net ecosystem CO2 exchange at three subtropical mangrove forests for 16 site-years, comprising two natural and one artificial forests. We employed a state-of-the-art data-driven modeling approach (i.e., Shapley additive explanations (SHAP) framework based on extreme gradient boosting model), which enabled us to explore the interactive effects of meteorological and tidal factors (e.g. salinity) with VPD on the mangrove NEP. We revealed that air temperature, global solar radiation (GR) and wind speed have significant interactions on the response of NEP to VPD stress in subtropical mangroves. For instance, when GR was high, the SHAP interaction values of VPD and GR on NEP decreased with increasing VPD, but when GR was low, the trends were the opposite. However, instead of identifying interactive effects between tidal salinity and VPD on mangrove NEP, we came across potential independent influence of salinity on the same. SHAP analysis was also able to disentangle the impact of VPD from other abiotic drivers. Thus, we evaluated the threshold effect of VPD stress on NEP loss in subtropical mangroves and observed a range of 2.50–2.95 kPa. Above this range, VPD stress leveled off. The subtropical mangrove responses to VPD should be therefore considered in the dynamic global vegetation models to increase the accuracy in carbon cycle simulations in the future.

Angstrom-Prescott Type Models for Predicting Solar Irradiation for Different Locations in Zimbabwe

Adequate assessment of solar radiation data is crucial for planning and designing solar energy systems. However, a major challenge facing solar energy technologies is the availability of solar radiation data at the specific area of interest. In this paper solar radiation and sunshine duration data from 29 stations in Zimbabwe were used to generate both monthly and annual Angstrom-Prescott (A-P) type coefficients, a and b, that are location based. The coefficients were developed using linear correlation between the clearness index and sunshine duration. The adaptation relationship between satellite and ground-measured irradiation had an R2 of 0.6738. The correlation between the clearness index and the sunshine duration in most of the stations was fairly high with the highest coefficient of determination, R2, of 0.9030. The A-Pregression coefficient, a, generated using the data from each station ranged between 0.2252 and 0.3976, whereas the regression coefficient, b, ranged between 0.3218 and 0.6265. The estimated and measured values of global solar radiation, He, and Hm, respectively from each station were compared using the mean absolute percentage error (MAPE), the root mean square error (RMSE), the mean absolute error (MAE) and the relative standard error (RSE). The MAE values for the models ranged from 0.5438 MJ/m2 to 2.2845 MJ/m2. The MAPE indicated a range between 2.5642 % and 10.334 %. The RSE ranged between 0.0346 % and 0.1537% while the RMSE for the models ranged from 0.7360 MJ/m2 to 2.9454 MJ/m2. The statistical indicators showed results that were within the recommended range for solar radiation predicting models from similar studies.

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

With the development of renewable energy, the exploitation and utilization of solar energy resources also need continuous progress, but solar radiation data shortage has become a serious concern. A method for estimating global solar radiation has been developed to address this issue. The sunshine-based model is currently the most widely used model due to its high calculation accuracy and few input parameters. This paper will first review 13 subcategories (8 categories in total) of the global solar radiation prediction model based on sunshine. Subsequently, the astronomical factors were introduced to modify empirical coefficients, and 8 new categories of models based on sunshine rate were introduced. The radiation data from 83 meteorological stations in China was used to train and validate the model, and the performance of the model was evaluated by using evaluation indicators, such as coefficient of determination (R2), root mean square error (RMSE), mean absolute bias error (MABE), mean bias error (MBE), and global performance index (GPI). The results show that the R2 value of the unmodified empirical model is in a range of 0.82–0.99, and the RMSE value is in a range of 0.018–3.09. In contrast, with the introduction of the astronomical factor, the model accuracy improves significantly, and the modified power function model (N3) gains its best performance. The R2 of model N3 is in a range of 0.86–0.99, and the RMSE value is in a range of 0.018–2.62. The R2 increases by 0.49%, while the RMSE value 6.44%. Above all, it does not require the input of other meteorological parameters for predicting the value of global solar radiation.

Estimation of Hourly Solar Radiations on Horizontal Surface from Daily Average Solar Radiations Using Artificial Neural Network

Hourly solar radiation information is necessary to increase the effectiveness of photovoltaic (PV) energy systems. However, compared with daily average solar radiation, the measurement of hourly solar radiation is much less available. In this study, a multilayer perceptron artificial neural network based on daily average solar radiation is proposed to estimate the amount of hourly solar radiation. The proposed method also relies on the location of the PV system, the hour when the estimate is needed, and the month when the estimate is needed. Two separate networks were built to estimate hourly direct solar radiation and hourly diffuse solar radiation, the summation of which is the estimated value of global hourly solar radiation. The networks were trained using three years of data from 2016 to 2018 from five locations around Japan. The data were taken from the website of the Japan Meteorological Agency (JMA). The number of hidden neurons for each network was determined by comparing the regression value obtained during the training process. The proposed method was validated by comparing the estimated value with the actual measured solar radiation value for each month in 2019 for the same five locations used for training the networks. The reliability of the proposed method was confirmed with the minimum R2 of 0.951 for the estimation of hourly direct solar radiation and 0.983 for hourly diffuse solar radiation. Further improvement in the accuracy of estimating the daily peak radiation value is considered to improve the total accuracy of the estimation model in the future.

Estimation of Global Solar Radiation (GSR) From the Sunshine Hour of Guranshe, Surkhet, Nepal

The variation in Global Solar Radiation (GSR) was studied by using experimental data via an automatic weather station (CMP3 pyranometer) located at Guranshe (Surkhet), a hilly area with elevation 2194m from the sea level. Also the estimated sunshine hour data of the area were used to calculate the GSR for the purpose of comparison with the measurements. Our study finds a good agreement between the measured (15.65 MJ/m2/day) and estimated/calculated (19.18 MJ/m2/day) values of annual average GSR. The estimated GSR uses Angstrom-Prescott type model for calculating sunshine hours, and the coefficients (a=0.28) and (b=0.57) were obtained using the Sangeetas and Tiwari model. The annual average estimated sunshine hours was found to be 6.86hr which is suitable for GSR based applications. The measured data were used to study the seasonal, monthly and diurnal variations of GSR. The maximum and minimum values of GSR were found during the spring and summer seasons respectively. The minimum GSR in summer is because of heavy rainfall, high relative humidity, and cloud formation in the sky during the time. The coefficient of regression(R) and the coefficient of determination (R2) were obtained as R=0.881 and R2=0.776 respectively. Here the high value of R (88.1%) indicates that of dependent variable (GSR) is nicely predicted by the independent variables. Also the coefficient of determination (R2) tells us the strength of the relationship between two variables. BIBECHANA 19 (2022) 150-159

DEVELOPMENT OF SUNSHINE BASED MODELS FOR ESTIMATING GLOBAL SOLAR RADIATION OVER KANO AND IKEJA, NIGERIA

In this present study, three (3) new sunshine based models were developed and evaluated using observed monthly average daily global solar radiation and sunshine hours meteorological variables spanning through thirty one years (1980-2010). The estimated global solar radiation values obtained from the empirical regression models for the developed models and nine (9) distinctive existing sunshine based models were compared through validation indicators of Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE), Index of Agreement (IA) and coefficient of determination (R2) allowing the identification and recommendation of the most accurate model suitable for the estimation of global solar radiation in Kano and Ikeja located in the Sahelian and Coastal regions respectively. The results in this present study revealed that the developed exponent exponential and quadratic latitude 2 sunshine based models were found more appropriate for estimation of global solar radiation in Kano (Latitude 12.05 and Longitude 8.20 ) and Ikeja (Latitude 6.58 and Longitude 3.33 ) respectively. The evaluated existing linear (1st order) and quadratic (2nd order) sunshine based models for Kano were found more suitable for the estimation of global solar radiation as compared with those found through literature survey. The empirical regression equations and the values of the validation indicators obtained in this study for each model varies significantly in each of the regions under investigation indicating that the twelve (12) sunshine based models are site – specific. The correlation between the

Spatiotemporal variations of global solar radiation: Case Study Egypt

The spatio-temporal characteristic of the available global solar radiation (GSR) variability is essential for effective grid integration of photovoltaic (PV) power systems, particularly in developing countries such as Egypt. Thus, the long-term spatio-temporal variability of GSR and its trend assessment, fluctuations, and abrupt change detection during the climate period 1985-2018 based on eight ground-based stations in Egypt were statistically analyzed. The missing records in the observed GSR data were completed using the SoDa (Solar radiation data) database after its validation at the selected eight stations, which produced high accuracy and slight bias compared to the available observations. The results showed that the northern coast, particularly the Nile Delta region, has lower GSR values than the southern region. At all stations, winter had the largest coefficient of variation (COV) values while summer had the lowest COV values. Furthermore, the trend analysis for GSR using Mann-Kendall (MK) rank statistical test revealed that autumn, followed by winter and spring has a positive trend across Egypt, while the annual and summer GSR have positive trends over middle and northern Egypt. The annual GSR long-term variability measured by Gaussian and Binomial low-path filters shows a positive trend at all stations except Arish, Asyut and Kharga. Moreover, the detected first abrupt change point for the annual GSR data occurred during the 1990s at all stations except for Matrouh in 2002. This first abrupt change point is positive (increasing GSR values) at all stations except a negative trend for Bahtim and Kharga. The second and third abrupt change points are positive at all stations except Arish during 2003-2009 in the second change point and returns to its positive trend in the third change point in 2010.

Study of Impact of Meteorological Parameters on Atmospheric Transmittance of Solar Radiation over Jumla

This paper reports the variation of atmospheric transmittance with meteorological parameters over Jumla (Lat.29.28° N, Long.:82.16° E and Alt.: 2300 m above sea level) from2011 to 2013 (three years) by using CMP6 pyranometer and satellite data. The trends of monthly and seasonal variations of atmospheric transmittance, solar insolation and clearness index have been analyzed. The result exemplifies that during the study period, average value of global solar radiation, solar insolation and clearness index are 19.26 ±3.88 MJ/m2/day , 4.95 ± 1.14 kWh/m2/day and 0.59 ±0.12 respectively. The average value of atmospheric transmittance during the whole study period is 0.60 ± 0.11. The average value of atmospheric transmittance of ozone, Rayleigh scattering, gas mixture, water vapor and aerosol are 0.9830 ±0.0007, 0.8999 ±0.0178, 0.9875 ± 0.0007, 0.8839 ±0.0101 and 0.7836 ±0.0909 respectively. There is positive correlation of relative sunshine hour and negative correlation of rain fall with atmospheric transmittance. Result of this research work is beneficial for the further analysis of solar radiation at different places improving life of flora and fauna and protecting the whole environment.

Novel models for photovoltaic output current prediction based on short and uncertain dataset by using deep learning machines

This paper presents deep learning neural network models for photovoltaic output current prediction. The proposed models are long short-term memory and gated recurrent unit neural networks. The proposed models can predict photovoltaic output current for each second for a week time by using global solar radiation and ambient temperature values as inputs. These models can predict the output current of the photovoltaic system for the upcoming seven days after being trained by half-day data only. Python environment is used to develop the proposed models, and experimental data of a 1.4 kWp PV system are used to train, validate and test the proposed models. Highly uncertain data with steps in seconds are used in this research. Results show that the proposed models can accurately predict photovoltaic output current whereas the average values of the root mean square error of the predicted values by the proposed LSTM and GRU are 0.28 A and 0.27 A (the maximum current of the system is 7.91 A). In addition, results show that GRU is slightly more accurate than LSTM for this purpose and utilises less processor capacity. Finally, a comparison with other similar methods is conducted so as to show the significance of the proposed models.

Performance analysis of a Silicon PV module (100W) in outdoor conditions: Experimental and Simulation study

In this paper, the incident solar radiation on horizontal and tilting surfaces was measured of a year using a pyranometer on the roof of Tanta University's Faculty of Science in Tanta city which is locating at Latitude (30° 41`). The average of daily global hourly solar radiation values on horizontal surfaces (H) and the global hourly solar radiation values on inclined surfaces (Ht) had been measured in the south direction of the sun for the meteorological variables. Miguel et al. correlation was used to determine hourly values of the beam and diffuse components of solar radiation (SR) from global solar irradiance. In order to attain best solar module performance throughout the year, the solar energy devices must be tilted south with a tilting angle equal to Tanta city latitude. The maximum value of Ht was 1174.15 Wm-2 in April and the minimum value of Ht was 816.11Wm-2 in October. The performance of 100 W solar silicon photovoltaic (PV) module in outdoor condition can be studied by depending on the incident values of H and Ht. The obtained results showed that the efficiencies of the 100 W solar PV module in winter, spring, summer and autumn were 4.29, 3.78, 7.56 and 4.58 %, respectively. The Maximum power point (Pmax) was calculated in July and its value was 45.98 W at solar noon and the minimum power point (Pmin) was calculated in October with value equal to 18.56 W at solar noon.

RENEWABLE ENERGIES RESOURCES EVALUATION USING A GEOGRAPHIC INFORMATION SYSTEMS IN THE COLOMBIAN CARIBBEAN REGION

This manuscript presents an integral evaluation of the use of wind and solar resources in the Colombian Caribbean region. For the use of solar and wind energy sources, spatial restrictions according to topography, natural parks, water reserves, indigenous and sacred reserves were taken into account. In addition, studies of the energy potential of wind and solar radiation were carried out through geostatistical analysis of different points in meteorological stations located in the region. Finally, areas with wind and solar potential were determined using the Geographic Information System for Renewable Energies (SIGER). The results show that the department of Guajira has the highest values of solar brightness (229-240 Month day), while the departments of Valledupar, Cesar, and part of Magdalena decrease in the range of 229 to 207 Month day. In terms of solar radiation, the departments of Guajira and Atlántico showed global solar radiation values of up to 6,015 W/m2. The departments of Cesar, Magdalena, and part of Bolivar showed values close to 5,259 W/m2; while Sucre, and Cordoba showed low solar radiation values of 4,502 W/m2. It is concluded that the departments of Atlántico and Guajira are excellent candidates for solar and wind energy projects due to their characteristics. The results of this manuscript are a fundamental basis for future technical-economic feasibility studies of renewable energy in the Colombian Caribbean region. In addition, it allows the elaboration of energy policies that encourage the execution of this type of study at a real level.Keywords: SIGER, renewable energies, solar energy, wind energy, wind potentialJEL Classification: Q42DOI: https://doi.org/10.32479/ijeep.11612

EMPIRICAL MODELS FOR CORRELATION OF CLEARNESS INDEX WITH CLOUD INDEX AT ZARIA, KADUNA STATE

In this study, the monthly average daily values of global solar radiation and relative sunshine hours on a horizontal surface over a period of five years (2011-2015) using multi-linear polynomial form of the AngstromPrescott model have been developed to estimate global solar radiation for Zaria (northern part of Nigeria) which lies on latitude 11°04'N and longitude 7o 42' E. Five different mathematical correlations models (first order, second order, exponential, powered, and logarithmic) was considered and it was found that first order, second order polynomials, exponential and powered gives a good model for estimating total solar radiation in Zaria. The agreement between the measured values (that obtained from the Nigerian Meteorological Agency) and the computed values is remarkable and the models are recommended for Zaria

Effect of climate change to solar energy potential: a case study in the Eastern Anatolia Region of Turkey.

Architects, hydrologists, agriculturists, and solar engineers require the data of solar radiation for solar technologies such as solar drying, cooking, heating, and building illuminations. The aim of this study is to evaluate the effect of climate change on the potential of solar energy in theEastern Anatolia Region (EAR) of Turkey. The global warming problem causedby greenhouse gases is increasing due to the increase in the use of fossil origin fuels in our world, and climate change iscoming out. In this content, the values of monthly sunshine duration and globalsolar radiation are provided by the Meteorological Service in Turkish for the EAR of Turkey in the periods between 1987 and 2010. Thus, in a period of 24 years, it is investigated how much change took place in meteorological data. These changes are examined in the two different periods. In conclusion, it is observed that important changes occur in some meteorological data. The highest decrease in the variation amount of yearly average global solar radiation is seen in Erzurum, while the highest increase is seen in Erzincan. The highest increase in the variation amount of yearly average sunshine duration is seen in Erzincan, while the highest decrease is seen in Bitlis. In addition, the statistical analysis (t-test) is made to determine whether the difference between two periods is statistically significant for a considered region.

Validation of meteorological and ground-level ozone WRF-CHIMERE simulations in a mountainous grapevine growing area for phytotoxic risk assessment

Ozone is the most damaging phytotoxic air pollutant to crop yield quantity and quality. This study presents the validation of a simulation with the WRF-CHIMERE modelling system in order to assess the risk of phytotoxicity by tropospheric ozone for an important and characteristic Mediterranean crop, i.e. the grapevine. The study region was the Douro wine region in Portugal, which is characterized by a rugged relief and a Mediterranean climate. The simulation covered a reference grapevine growing season in the Northern Hemisphere (from April to September 2017), during which a particular measuring campaign was also carried out. The validation of the meteorological simulations on a daily and hourly time resolution was performed based on data from three weather stations, namely on temperature, global solar radiation, relative humidity, wind speed and direction values. The ozone phytotoxicity was assessed with data from two measuring stations. A specific grapevine growth parameter based on monitored phenological observations was introduced for ozone stomatal uptake assessment. Concerning meteorology, validation statistics were acceptable and within the range of what has been found in other regional climate modelling simulations. Ground-level ozone-based values were calculated for a better assessment of the phytotoxic risk, in particular cumulative standards for vegetation protection. Stomatal flux estimates were within the range of those measured for the local cultivars in the field campaign when there was not severe water stress limitation. Both field and statistically adjusted model values indicate that considerable areas in the Demarcated Douro Region of Portugal can exceed the critical exposure values for vegetation according to current European legislation standards. Moreover, measured and simulated results indicate an ozone impact on grapevine yield and quality in the target region because the exposure- and flux-based indices exceed the criteria based on current open-top-chamber experimental knowledge.

Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks

Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising solar energy systems. In the case of rarity or absence of these measurements, it is important to have a theoretical or empirical model to compute the GSR values. Therefore, the main goal of this work is to offer, to designers and engineers of solar energy systems, an appropriate and accurate way to predict the half-hour global solar radiation (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed, precipitation, and acquisition time vector in half-hour scale). For that purpose, two intelligent models are developed: the first one is a multivariate dynamic neural network with feedback connection, and the second is a multivariate static neural network. The database used to build these models was recorded in Agdal’s meteorological station in Marrakesh, Morocco, during the years of 2013 and 2014, and it was divided into two subsets. The first subset is used for training and validating the models, and the second subset is used for testing the efficiency and the robustness of the developed models. The obtained results, in terms of the statistical performance indicators, demonstrate the efficiency of the developed forecasting models to accurately predict the HHGSR parameter in the city of Marrakesh, Morocco.

Prediction of daily global solar radiation using different empirical models on the basis of meteorological parameters at Trans Himalaya Region, Nepal

Global Solar Radiation (GSR) is the cleanest and freely available energy resource on the earth. GSR was measured for six years (2010 -2015) at the horizontal surface using calibrated first-class CMP6 pyranometer at Kathmandu (Lat. 27.70o N, Long. 85.5oE and Alt. 1350m). This paper explains the daily, monthly, and seasonal variations of GSR and also compares with sunshine hour, ambient temperature, relative humidity, and precipitation to GSR. The annual average global solar radiation is about 4.16 kWh/m2/day which is a significant amount to promote solar active and passive energy technologies at the Trans-Himalaya region. In this study, the meteorological parameters are utilized in the regression technique for four different empirical models and finally, the empirical constants are found. Thus obtained coefficients are utilized to predict the GSR using meteorological parameters for the years to come. In addition, the predicted GSR is found to be closer to the measured value of GSR. The values are justified by using statistical tools such as coefficient of determination (R2), root mean square error (RMSE), mean percentage error (MPE), and mean bias error (MBE). Finally, the values of R2, RMSE, MPE, and MBE are found to be 0.792, 1.405, -1.014, and 0.011, respectively for the model (D), which are based on sunshine hour, temperature and relative humidity. In this model, the empirical constants, a = 0.155, b = 0.134, c = 0.014 and d = 0.0007 are determined which can be utilized at the similar geographical locations of Nepal.
 BIBECHANA 18 (2021) 159-169

Study of trend and fluctuations of global solar radiation over Egypt

ABSTRACT Climatological spatiotemporal variability of global solar radiation (GSR) and its trend analysis, fluctuations and abrupt changes based on seven sites (Cairo, Arish, Barrani, Matrouh, Aswan, Asyut, Kharga) in Egypt were studied during the period 1985–2018. Fifth-generation dataset of European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis of the global climate and weather for the past 4 to 7 decades (ERA5) data after validation with available observed GSR data has been used. Monthly, seasonal and annual GSR values have marked variations. The results revealed that the highest values of coefficient of variation occurred at stations in winter, while the lowest values occurred in summer. Moreover, in winter and spring, all stations presented a positive Mann-Kendell (MK) trend and almost all stations in annual except Aswan, Asyut and Kharga, whereas in autumn, all station presented a negative MK trend, summer in all stations except Barrani and Cairo. The fluctuations in the annual GSR were investigated using the cumulative sum charts (CUSUM) method, where all stations have alternating trend between negative and positive CUSUM along period.

Modelagem matemática aplicada a evapotranspiração de referência para a cidade de Januária (MG)

A Modelagem Matemática proporciona modelar situações cotidianas para uma melhor interpretação dos eventos. Contribui, também, com o desenvolvimento acadêmico e busca por soluções a fim de facilitar problemas de áreas distintas. Para melhor aproveitamento dos recursos hidrícos na região do Norte de Minas Gerais, o presente trabalho objetivou-se em determinar a média mensal da evapotranspiração de referência (ET0) pelo método Penman Monteith. O saldo de radiação (R_n) correspondeu a 59; 0% do valor médio da radiação solar global. A variação da evapotranspiração oscilou entre os valores 6,82 mm/dia e 2,57 mm/dia, obtendo o maior coeficiente de determinação com a radiação líquida em que R^2 é igual 0,682. No intervalo entre 3,5 e 5,5 mm/dia concentra-se uma amostra considerável das evapotranspirações de referência ocorrentes em Januária (MG).