Retrieving daily global solar radiation from routine climate variables

Solar radiation is an important variable for studies related to solar energy applications, meteorology, climatology, hydrology, and agricultural meteorology. However, solar radiation is not routinely measured at meteorological stations; therefore, it is often required to estimate it using other techniques such as retrieving from satellite data or estimating using other geophysical variables. Over the years, many models have been developed to estimate solar radiation from other geophysical variables such as temperature, rainfall, and sunshine duration. The aim of this study was to evaluate six of these models using data measured at four independent worldwide networks. The dataset included 13 stations from Australia, 25 stations from Germany, 12 stations from Saudi Arabia, and 48 stations from the USA. The models require either sunshine duration hours (Ångstrom) or daily range of air temperature (Bristow and Campbell, Donatelli and Bellocchi, Donatelli and Campbell, Hargreaves, and Hargreaves and Samani) as input. According to the statistical parameters, Ångstrom and Bristow and Campbell indicated a better performance than the other models. The bias and root mean square error for the Ångstrom model were less than 0.25 MJ m² day^?1 and 2.25 MJ m² day^?1, respectively, and the correlation coefficient was always greater than 95 %. Statistical analysis using Student’s t test indicated that the residuals for Ångstrom, Bristow and Campbell, Hargreaves, and Hargreaves and Samani are not statistically significant at the 5 % level. In other words, the estimated values by these models are statistically consistent with the measured data. Overall, given the simplicity and performance, the Ångstrom model is the best choice for estimating solar radiation when sunshine duration measurements are available; otherwise, Bristow and Campbell can be used to estimate solar radiation using daily range of air temperature.     

Precise estimation of hourly global solar radiation for micrometeorological analysis by using data classification and hourly sunshine

We have developed a method for estimating hourly global solar radiation (GSR) from hourly sunshine duration data. This procedure requires only hourly sunshine duration as the input data and utilizes hourly precipitation and daily snow cover as auxiliary data to classify time intervals into six cases according to weather conditions. To obtain hourly GSR using a simple algebraic form, a quadratic function of the solar elevation angle and the sunshine duration ratio is used. Daily GSR is given by a sum of hourly GSRs. We evaluated the performance of the newly developed method using data obtained at 67 meteorological stations and found that the estimated GSR is highly consistent with that observed. Hourly and daily root-mean-square misfits are approximately 0.2 MJ/m²/h (~55 W/m²) and 1.4 to 1.5 MJ/m²/day (~16 to 17 W/m²), respectively. Our classification of weather conditions is effective for reducing estimation errors, especially under cloudy skies. Since the sunshine duration is observed at more meteorological stations than GSR, the proposed new method is a powerful tool for obtaining solar radiation with hourly resolution and a dense geographical distribution. One of the proposed methods, GSRgrn, can be applicable to hourly GSR estimations at different observation sites by setting local parameters (the precipitable water, surface albedo, and atmospheric turbidity) suitable to the sites. The hourly GSR can be applied for various micrometeorological studies, such as the heat budget of crop fields.     

Simulation and Regionalization of Daily Global Solar Radiation: A Case Study in Quebec,Canada

Global solar radiation (GSR) is essential for agricultural and plant growth modelling, air and water heating analyses, and solar electric power systems. However, GSR gauging stations are scarce compared with stations for monitoring common meteorological variables such as air temperature and relative humidity. In this study, one power function, three linear regression, and three non-linear models based on an artificial neural network (ANN) are developed to extend short records of daily GSR for meteorological stations where predictors (i.e., temperature and/or relative humidity) are available. The seven models are then applied to 19 meteorological stations located across the province of Quebec (Canada). On average, the root-mean-square errors (RMSEs) for ANN-based models are 0.33–0.54?MJ?m^?2?d^?1 smaller than those for the power function and linear regression models for the same input variables, indicating that the non-linear ANN-based models are more efficient in simulating daily GSR. Regionalization potential of the seven models is also evaluated for ungauged stations where predictors are available. The power function and the three linear regression models are tested by interpolating spatially correlated at-site coefficients using universal kriging or by applying a leave-one-out calibration procedure for spatially uncorrelated at-site coefficients. Regional ANN-based models are also developed by training the model based on the leave-one-out procedure. The RMSEs for regional ANN models are 0.08–0.46?MJ?m^?2?d^?1 smaller than for other models using the same input conditions. However, the regional ANN-based models are more sensitive to new station input values compared with the other models. Maps of interpolated coefficients and regional equations of the power function and the linear regression models are provided for direct application to the study area.     

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

Long-term,ground-based daily global solar radiation (DGSR) at Zhongshan Station in Antarctica can quantitatively reveal the basic characteristics of Earth’s surface radiation balance and validate satellite data for the Antarctic region.The fixed station was established in 1989,and conventional radiation observations started much later in 2008.In this study,a random forest (RF) model for estimating DGSR is developed using ground meteorological observation data,and a highprecision,long-term DGSR dataset is constructed.Then,the trend of DGSR from 1990 to 2019 at Zhongshan Station,Antarctica is analyzed.The RF model,which performs better than other models,shows a desirable performance of DGSR hindcast estimation with an R~2 of 0.984,root-mean-square error of 1.377 MJ m~(-2),and mean absolute error of 0.828 MJ m~(-2).The trend of DGSR annual anomalies increases during 1990–2004 and then begins to decrease after 2004.Note that the maximum value of annual anomalies occurs during approximately 2004/05 and is mainly related to the days with precipitation (especially those related to good weather during the polar day period) at this station.In addition to clouds and water vapor,bad weather conditions (such as snowfall,which can result in low visibility and then decreased sunshine duration and solar radiation) are the other major factors affecting solar radiation at this station.The high-precision,longterm estimated DGSR dataset enables further study and understanding of the role of Antarctica in global climate change and the interactions between snow,ice,and atmosphere.     

Simple new methods to estimate global solar radiation based on meteorological data in Egypt

Three simple methods to estimate global solar radiation are proposed in addition to (Solar Energy 63 (1998) 147). All were tested seasonally and at different sky conditions at seven locations in Egypt. The methods use ground-based measurements of maximum and minimum temperature, daily mean of cloud cover and extraterrestrial global radiation. Average of root mean square differences (RMSD) for a comparison between observed and estimated global radiation for all locations tested was around 10% for the new methods and 13% for Supit–Van Kappel method. The coefficient of determination R² is higher for the new methods for all tested locations. Better results were obtained when applying the new methods to different seasons. The differences in root mean square error (RMSE) between the new methods and Ångstrom–Prescott method that is based on sunshine duration data were less than 1.0 MJ m⁻² day⁻¹ at all sites. On the whole, the performance statistics demonstrate that the new methods are better when compared by Ångstrom–Prescott method.     

Analysis of solar radiation over Egypt

Summary  The database utilized in this analysis consisted of daily sunshine duration and hourly global and diffuse radiation on a horizontal surface (for Matruh Cairo, and Aswan), and normal incidence beam radiation (for Cairo and Aswan only). Monthly-average hourly and daily values are reported for each of these three types of measured radiation, together with the calculated monthly-average daily values for the components of global radiation, horizontal beam and diffuse radiation. The monthly-average hourly and daily clearsky index values have also been calculated and analyzed. Monthly-average daily frequency distributions of the clearsky index values are reported for each month. The annual-average daily global irradiation values are 19.4, 18.67, and 21.78 MJ/m² and for diffuse irradiation they are 6.34, 6.65 and 6.23 MJ/m² for Matruh, Cairo and Aswan, respectively. For the normal incidence beam irradiation the annual-average daily values are 16.94 and 24.46 MJ/m² for Cairo and Aswan, respectively. The annual-average daily fractions of the direct component of horizontal global radiation are 0.70, 0.61 and 0.72 for the three stations, respectively. The annual-average daily values for the clearsky index are 0.585, 0.566, and 0.648, and the average frequency of clear days annually are 67.3, 42.3 and 77.6% respectively. The annual variations and trend analysis were analyzed for daily global, direct, and diffuse radiation on a horizontal surface, daily sunshine duration, and for the daily ratios G/G₀, and D/G for the stations Matruh, Cairo and Aswan. The distribution of these components of radiation and their ratios over the study stations in Egypt is also discussed. The results show that Egypt is characterized by relatively high average-daily radiation rates, both global and direct, and a relatively high frequency of clear days. Cairo, due to its urbanization and high pollution, has relatively low average-daily radiation rates, particularly in direct radiation, and the frequency of clear days. Received February 26, 1998 Revised February 4, 1999     

Analysis of solar radiation on the surface estimated from GWNU solar radiation model with temporal resolution of satellite cloud fraction

Preliminary analysis with a solar radiation model is generally performed for photovoltaic power generation projects. Therefore, model accuracy is extremely important. The temporal and spatial resolutions used in previous studies of the Korean Peninsula were 1 km × 1 km and 1-h, respectively. However, calculating surface solar radiation at 1-h intervals does not ensure the accuracy of the geographical effects, and this parameter changes owing to atmospheric elements (clouds, aerosol, ozone, etc.). Thus, a change in temporal resolution is required. In this study, one-year (2013) analysis was conducted using Chollian geostationary meteorological satellite data from observations recorded at 15-min intervals. Observation data from the intensive solar site at Gangneung-Wonju National University (GWNU) showed that the coefficient of determination (R²), which was estimated for each month and season, increased, whereas the standard error (SE) decreased when estimated in 15-min intervals over those obtained in 1-h intervals in 2013. When compared with observational data from 22 solar sites of the Korean Meteorological Administration (KMA), R² was 0.9 or higher on average, and over- or under-simulated sites did not exceed 3 sites. The model and 22 solar sites showed similar values of annual accumulated solar irradiation, and their annual mean was similar at 4,998 MJ m^?2 (3.87 kWh m^?2). These results show a difference of approximately ± 70 MJ m^?2 (± 0.05 kWh m^?2) from the distribution of the Korean Peninsula estimated in 1-h intervals and a higher correlation at higher temporal resolution.     

支持向量机方法在南京太阳总辐射推算中的应用

利用1981、1996和2001年逐日南京站太阳总辐射和日照时数观测资料,建立了基于支持向量机(support vector machine,SVM)方法的太阳总辐射推算模型,预测了1982、1997和2002年的太阳总辐射,并把推算结果和采用线性的气候学方法所得到的推算结果分别与实测值进行对比。采用线性方法得到的1982、1997和2002年的太阳总辐射预测值与实测值间基于1:1线的决定系数(R~2)分别为0.800、0.859和0.838,均方根误差(RMSE)分别为3.250、2.649和2.925 MJ·m~(-2)·d~(-1)。采用SVM方法得到的1982、1997和2002年的R~2分别为0.894、0.938和0.936,RMSE分别为2.353、1.726和1.804 MJ·m~(-2)·d~(-1)。SVM方法得到的太阳总辐射预测值与实测值之间的误差较小,预测精度高于线性方法,更适用于实际太阳总辐射的计算。     

江苏省太阳能资源评估

采用1：25万DEM数据和常规气象站观测资料,实现了江苏省100mX100m分辨率太阳总辐射量分布式模拟,并分析了江苏省太阳总辐射量的时空分布规律。结果表明：江苏省气候平均太阳总辐射量为4749MJ／m2,呈现由西南向东北递增的特点,连云港市最高（5063MJ／m2）,无锡市最低（4514MJ／m2）。太阳总辐射量在年内变化特点为,5月最高,12月最低。结合常规气象站日照时数观测资料,从年日照时数、年日照时数i〉6h的天数以及日照时数〉16h的最多天数月份与最少天数月份的天数的比值分析了江苏省太阳能资源的稳定度特征,其总体规律依然是西南至东北走向,即江苏省东北部地区太阳能资源开发利用优势最高。     

Parameterisation of incoming longwave radiation over glacier surfaces in the semiarid Andes of Chile

A good understanding of radiation fluxes is important for calculating energy, and hence, mass exchange at glacier surfaces. This study evaluates incoming longwave radiation measured at two nearby glacier stations in the high Andes of the Norte Chico region of Chile. These data are the first published records of atmospheric longwave radiation measurements in this region. Nine previously published optimised parameterisations for clear sky emissivity all produced results with a root mean square error (RMSE) ~20 W?m^?2 and bias within ±5 W m^?2, which is inline with findings from other regions. Six optimised parameterisations for incoming longwave in all sky conditions were trialled for application to this site, five of which performed comparably well with RMSE on daytime data <18 W?m^?2 and bias within ±6 W?m^?2 when applied to the optimisation site and RMSE <20 W?m^?2 and bias within ±10 W m^?2 when applied to the validation site. The parameterisation proposed by Mölg et al. (J Glaciol 55:292-302, 2009) was selected for use in this region. Incorporating the proposed elevation modification into the equation reduced the bias in the modelled incoming longwave radiation for the validation site. It was found that applying the parameterisation optimised in the original work at Kilimanjaro produced good results at both the primary and validation site in this study, suggesting that this formulation may be robust for different high mountain regions.     

Estimating sunshine duration from other climatic data by artificial neural network for ET0 estimation in an arid environment

Sunshine duration data are desirable for calculating daily solar radiation (R _s) and subsequent reference evapotranspiration (ET₀) using the Penman–Monteith (PM) method. In the absence of measured R _s data, the Ångström equation has been recommended by the Food and Agriculture Organization (FAO) of the United Nations. This equation requires actual sunshine duration that is not commonly observed at many weather stations. This paper examines the potential for the use of artificial neural networks (ANNs) to estimate sunshine duration based on air temperature and humidity data under arid environment. This is important because these data are commonly available parameters. The impact of the estimated sunshine duration on estimation of R _s and ET₀ was also conducted. The four weather stations selected for this study are located in Sistan and Baluchestan Province (southeast of Iran). The study demonstrated that modelling of sunshine duration through the use of ANN technique made acceptable estimates. Models were compared using the determination coefficient (R ²), the root mean square error (RMSE) and the mean bias error (MBE). Average R ², RMSE and MBE for the comparison between measured and estimated sunshine duration were calculated resulting 0.81, 6.3 % and 0.1 %, respectively. Our analyses also demonstrate that the difference between the measured and estimated sunshine duration has less effect on the estimated R _s and ET₀ by using Ångström and FAO-PM equations, respectively.     

The assessment of aerosol optical properties over Mohal in the northwestern Indian Himalayas using satellite and ground-based measurements and an influence of aerosol transport on aerosol radiative forcing

The present study deals with the aerosol optical properties which are assessed during the period 2007 to 2009 over Mohal (31.9oN, 77.12oE) in the northwestern Indian Himalaya, using ground-based measurements and multi-satellite data. The daily average value of aerosol optical depth (AOD) at 500?nm, ?ngstr?m exponent and turbidity coefficient are 0.24?±?0.08, 1.02?±?0.34 and 0.13?±?0.05, respectively. The comparative study of satellite and ground-based measurements reveals that the percentage retrieval for daily AOD at 550?nm over Mohal within the expected accuracy (???? _p?? ?=?±0.05?±?0.15?? _p?? ) is around 87%, with a significant correlation coefficient of 0.76. The present study suggests that the retrieval of AOD through satellite data is able to characterise the distribution of AOD over Mohal. However, further efforts are needed in order to eliminate systematic errors in the existing Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm. The transport of desert dust and anthropogenic aerosol during high aerosol loading days caused a significant reduction in surface-reaching solar radiation by 149 and 117%, respectively. This large reduction in surface-reaching solar radiation increased the atmospheric heating rate by 0.93 and 0.72?K?day^?1, respectively. This study indicates significant climatic implications due to the transport of aerosols in the northwestern Indian Himalaya.     

2011年2月—2012年1月东南极高原辐射平衡观测研究

利用东南极高原熊猫-1自动气象站2011年2月—2012年1月观测的辐射资料和相关资料,对辐射分量和辐射平衡的季节变化进行了研究。结果表明,夏季是东南极高原获得太阳能的主要时段,总辐射通量夏季平均为365.0 W/m²,总量达到2752.1 MJ/m²,占全年总辐射量的58%。各个季节均能出现总辐射瞬时值大于大气顶水平总辐射,春季发生频率最高,冬季最小,总辐射平均日变化呈单峰型。大气长波辐射除夏季外,日变化不明显。冰雪面长波辐射除冬季外,各季节平均日变化呈明显的单峰单谷型。净辐射12月和1月为很小的正值,其他月份为负值。年平均净辐射为 -8.7 W/m²,表明地表相对于大气为冷源。该站的辐射平衡特征与其他南极内陆高原站相似,雪面具有强烈的辐射冷却效应,导致净辐射绝对值都小于下降风区。     

山东禹城紫外辐射变化特征及其估测方程的建立

本文对2005～2011年山东禹城地区观测得到的紫外辐射的时间变化特征及紫外辐射与总辐射比值的变化特征进行了分析, 并结合气温、降水和露点温度资料建立了禹城地区的紫外辐射估测方程。结果表明:紫外辐射日累计值的变化范围为0.10～1.20 MJ m-2 d-1, 年平均值为0.468 MJ m-2 d-1;紫外辐射日、季节变化规律与总辐射一致, 季节变化都表现为冬季小夏季大, 最小值出现在1月, 最大值出现在6月, 日变化则呈现早晚小中午大的特征;紫外辐射与总辐射的比值范围为0.023～0.046, 其季节变化特征也是冬季小夏季大, 该比值随晴空指数的增大而减小, 而在晴空指数大于0.5时比较稳定。利用温度日较差(日最高气温与最低气温的差值)建立了紫外辐射估测方程, 决定系数R2达0.80, 平均相对误差为0.19, 估测紫外线等级与实测紫外线等级相差不大于1的数据占95%, 该方法可以较好地进行紫外辐射等级的估测。     

Characteristics of UV radiation at Tazhong of the Tarim Basin,west China

Tazhong station, located at the hinterland of the Taklimakan Desert in northwest China, experiences frequent dusty weather events during spring and summer seasons (its dusty season) caused by unstable stratified atmosphere, abundant sand source and strong low-level wind. On average, it has 246.2 dusty days each year, of which 16.2 days are classified as sand and dust storm days. To better understand the characteristic of solar ultraviolet (UV) radiation and factors influencing its variations under such an extreme environment, UV radiation data were collected continuously from 2007 to 2011 at Tazhong station using UVS-AB-T radiometer by Kipp and Zonen. This study documents observational characteristics of the UV radiation variations observed during the five-year period. Monthly UV radiation in this region varied in the range of 14.1–37.8 MJ m^?2 and the average annual amount was 320.7 MJ m^?2. The highest value of UV radiation occurred in June (62.5 W m^?2) while the lowest one in December (29.3 W m^?2). It showed a notable diurnal cycle, with peak value at 12:00–13:00 LST. Furthermore, its seasonal variation exhibited some unique features, with averaged UV magnitude showing an order of summer > spring > autumn > winter. The seasonal values were 37.0, 29.1, 24.9 and 15.9 MJ m^?2, respectively. In autumn and winter, its daily variations were relatively weak. However, significant daily variations were observed during spring and summer associated with frequent dust weather events occurring in the region. Further analysis showed that there was a significant correlation between the UV radiation and solar zenith angle under different weather conditions. Under the same solar zenith angle, UV radiation was higher during clear days while it was lower in sand and dust storm days. Our observations showed that there was a negative correlation between UV radiation and ozone, but such a relationship became absent in dusty days. The UV radiation was reduced by 6 % when cloud amount was 1–4 oktas, by 12 % when the cloud amount was 5–7 oktas, and by 24 % when the cloud amount was greater than 8 oktas. The relative reduction of UV radiation reached 26, 38, and 45 % in dust day, blowing sand day and sand and dust storm day, respectively. The results revealed that decrease in UV radiation can be attributed to cloud coverage and dust aerosols. Moreover, the reduction of UV radiation caused by dust aerosols was about 2–4 times greater than that caused by cloud coverage. These observational results are of value for improving our understanding of processes controlling UV radiation over sand desert and developing methods for its estimation and prediction.     

Relationship between Net Radiation and Broadband Solar Radiation in the Tibetan Plateau

The characteristics of net radiation (R_n)(0.3--10 μm) in Lhasa and Haibei in the Tibetan Plateau were analyzed based on long-term in-situ measurements of surface radiation data. The monthly average of daily R_n reached a minimum during the winter period followed by an increase until May and then a decline until January. This variation is consistent with solar activity. The annual mean daily total R_n values were 0.92 MJ m^-2 d^-1 and 0.66 MJ m^-2d^-1 in Lhasa and Haibei, respectively. A relationship between R_n and broadband solar radiation (R_s) was demonstrated by a good linear correlation at the two sites. R_n can be an accurate estimate from R_s. The estimated R_n values were similar to the observed values, and the relative deviations between the estimates and measurements of R_n were 2.8% and 3.8% in Lhasa and Haibei, respectively. The application of the R_n estimating model to other locations showed that it could provide acceptable estimated R_n values from the R_s data. Furthermore, we analyzed the influence of clouds on R_n by different clear index (K_s), defined as the ratio of R_s to the extraterrestrial solar irradiance on a horizontal surface. The results indicate that more accurate results are associated with increased cloudy conditions. The influence of the albedo was also considered, but its inclusion in the model resulted in only a slight improvement. Because surface albedo is not usually measured, an expression based solely on global solar radiation could be of more extensive use.     

宝坻太阳辐射资料可用性研究

应用典型的辐射资料质量检验方法、辐射数据变化特征分析、人工与器测日照对比分析及太阳总辐射与相关辐射要素间的统计分析对天津市宝坻国家级基本气象站站内的太阳辐射观测系统试运行期间的辐射观测数据进行了质量分析,结果表明,试运行期间数据到报情况理想,总、散射辐射观测数据的BSRN的质量检验合格率为100%,直接辐射合格率为85%,净辐射通过了仪器阀值质量检验;太阳辐射值及变化特征符合理论实际;人工与器测日照时数具有很好的线性相关性(R2=0.96),总辐射与日照时数及散射辐射之间的线性变化与历史经验结论吻合。总体来看,宝坻太阳辐射系统观测数据可用性较高,能够满足日常业务需求。     

Estimating daily global solar radiation during the growing season in Northeast China using the ?ngstr?m–Prescott model

Daily global solar radiation is an important input required in most crop models. In the present study, a sunshine-based model, the ?ngstr?m–Prescott model, is employed to estimate daily global solar radiation on a horizontal surface during the growing season in Northeast China. Data from six control groups are used. The controls include the entire sequence, precipitation days, and non-precipitation days both during the growing season and year-round. Estimations are validated by comparing the calculated values with the corresponding measured values. The results indicate that estimating daily global solar radiation during the growing season using data only from the growing season is better than using year-round data. Classifying days with respect to precipitation and non-precipitation is also unnecessary. The performance on estimating daily global solar radiation during the growing season using the entire data in growing season performs best. A sunshine-based equation is obtained using our method to estimate growing season daily radiation for all meteorological stations in Northeast China. The approved approach is expected to be beneficial to crop models and other agricultural purposes.     

Anthropogenic heat in the city of S?o Paulo, Brazil

The main goal of this work is to describe the anthropogenic energy flux (Q _F) in the city of S?o Paulo, Brazil. The hourly, monthly, and annual values of the anthropogenic energy flux are estimated using the inventory method, and the contributions of vehicular, stationary, and human metabolism sources from 2004 to 2007 are considered. The vehicular and stationary sources are evaluated using the primary consumption of energy based on fossil fuel, bio fuel, and electricity usage by the population. The diurnal evolution of the anthropogenic energy flux shows three relative maxima, with the largest maxima occurring early in the morning (??19.9 Wm^?2) and in the late afternoon (??20.3 Wm^?2). The relative maximum that occurs around noontime (??19.6 Wm^?2) reflects the diurnal pattern of vehicle traffic that seems to be specific to S?o Paulo. With respect to diurnal evolution, the energy flux released by vehicular sources (Q _FV) contributes approximately 50% of the total anthropogenic energy flux. Stationary sources (Q _FS) and human metabolism (Q _FM) represent about 41% and 9% of the anthropogenic energy flux, respectively. For 2007, the monthly values of Q _FV, Q _FS, Q _FM, and Q _F are, respectively, 16.8?±?0.25, 14.3?±?0.16, 3.5?±?0.03, and 34.6?±?0.41?MJ?m^?2?month^?1. The seasonal evolution monthly values of Q _FV, Q _FS, Q _FM, and Q _F show a relative minimum during the summer and winter vacations and a systematic and progressive increase associated with the seasonal evolution of the economic activity in S?o Paulo. The annual evolution of Q _F indicates that the city of S?o Paulo released 355.2?MJ?m^?2?year^?1 in 2004 and 415.5?MJ?m^?2?year^?1 in 2007 in association with an annual rate of increase of 19.6?MJ?m^?2?year^?1 (from 2004 to 2006) and 30.5?MJ?m^?2?year^?1 (from 2006 to 2007). The anthropogenic energy flux corresponds to about 9% of the net radiation at the surface in the summer and 15% in the winter. The amplitude of seasonal variation of the maximum hourly value of the diurnal variation increases exponentially with latitude.     

The Influence of Selected Meteorological Parameters on the Concentration of Surface Ozone in the Central Region of Poland

Abstract?This paper presents the results of measurements of the concentration of surface ozone and concurrent standard meteorological parameters: total solar radiation, temperature, relative humidity, pressure, wind speed, and vertical and horizontal components of the wind. The data were collected from 2005 to 2010 at stations located in central Poland (Mazowieckie voivodeship): Warszawa (urban), Legionowo (suburban), Granica and Belsk (rural). Furthermore, Granica is situated in the forested area of Kampinoski National Park. Continuously measured surface ozone concentrations demonstrated the well-known diurnal cycle of surface ozone concentration with a maximum in the afternoon and a minimum in the early morning hours. The averaged diurnal variations over six years reveal that the highest concentrations appear at rural stations (Belsk: 55?µg?m^?3 and Granica: 50?µg?m^?3) and the lowest at the urban station (Warszawa: 41?µg?m^?3). The threshold for high levels of surface ozone (120?µg?m^?3 per 8?h) was exceeded most often at Granica and Belsk. The occurrence of the ozone “weekend effect,” especially at urban stations, has been identified. The difference between weekend and weekday surface ozone concentrations at urban and rural stations was as high as 6.5?µg?m^?3 and approximately 2?µg?m^?3, respectively. Using appropriate statistical tools, it has been shown that meteorological conditions have a significant influence on ozone concentration. High correlation coefficients were found between ozone concentration and solar radiation, temperature, relative humidity, and wind speed. The forward stepwise regression model explains up to 75% of the variations in daily surface ozone concentration in terms of meteorological variability in summer and up to 70% in winter. At the same time, a multilayer perceptron neural network model was used to reconstruct the concentration of surface ozone. High correlation coefficients (up to 0.89) indicate that, on the basis of standard meteorological parameters and NO₂ concentration, we can determine ozone concentration with high accuracy.