基于空气污染指数的太阳日总辐射计算方法

通过对2001—2012年全国23个站实测资料的分析,利用非线性回归法建立了以气温日较差、天文日照百分率和空气污染指数为主导因子的太阳日总辐射模型,这里简称为DSRM-Y模型 (Daily Solar Radiation Model-Y),检验其效果并与已有的DSRM-C模型 (Daily Solar Radiation Model-C) 进行效果比对。结果表明:太阳日总辐射与空气污染指数呈显著负相关,DSRM-Y模型的太阳日总辐射估算值与实测值的散点图以及平均偏差、均方根误差、误差分析均表现出较好的拟合效果。将模型应用于西宁、上海、昆明3个代表站,空气污染指数上升后,3个站太阳日总辐射均呈减少趋势;23个站DSRM-Y模型的均方根误差均小于DSRM-C模型,即DSRM-Y模型的拟合效果好于DSRM-C模型。     

宁夏区域太阳日辐射通量计算方法的研究

利用银川站过去5 a的太阳日辐射观测资料(1981~1985)与大气外太阳辐射、日照时数、日照长度间的相关关系,确定了区域系数as。通过对bs的取值进行敏感测试,可得到一组最佳推算太阳辐射通量的区域系数:as=0.3,bs=0.5。用此系数和太阳日辐射通量计算公式,推算了银川站1986、1987年太阳日辐射通量并用观测值进行验证,结果表明:两者之间有很好的线性相关,R2=0.94,验证了区域系数的可信度。通过对银川站2 a(1986,1987)资料的平均误差、平均偏差、平均绝对偏差和均方根偏差的计算表明,结果与国内相关报道基本一致。对宁夏永宁站1989~2000年的太阳日辐射通量用区域系数进行估算,并与银川站的实际观测资料比较,结果显示永宁站太阳日辐射通量估算值和银川站实测值间有很好的线性关系,12 a间的方差最小值R2=0.88。     

1961~2010年重庆地区气温和总辐射变化分析

基于重庆地区34个气象台站1961²010年的日照时数、平均气温数据,结合该区域唯一的沙坪坝辐射站总辐射数据,分析了重庆地区气温、总辐射的时空变化特征,结果表明:1)50年间,重庆地区气温呈上升趋势而总辐射呈下降趋势。两者在年际变化上显著正相关,而在年代际变化上则表现波动。空间上重庆西部、东南部偏南地区以及东北部大部地区增温显著,而总辐射减少最多;2)由沙坪坝辐射站数据分析,晴空指数与日照百分率高度相关,可以利用日照百分率数据,推算其他台站辐射数据,用于相关研究。     

近50年安徽省太阳总辐射的时空变化特征

采用1961—2010年安徽省辐射观测数据和常规气象要素观测资料,建立了太阳总辐射的气候学计算方法;进而推算了安徽省各地太阳总辐射,并采用趋势分析、突变检验和小波分析等方法研究了其时空变化特征。结果表明:以理论天文辐射为起始值所建立的全省统一公式,能够较好的拟合安徽省月尺度的太阳总辐射值。根据公式推算的安徽省各地太阳总辐射资源的丰富程度以3级为主,空间分布呈北多南少的特征,季节分布为夏多冬少单峰型,但在梅雨期存在波谷。近50年来安徽省各地太阳总辐射量基本呈一致的减少趋势,全省平均下降趋势为每10年减少0.31 MJ·m-2·d-1,近年来辐射下降趋缓。安徽省太阳总辐射在20世纪80年代初存在一次突变现象;近50年总辐射量以准10年和4~6年左右周期振荡较为明显,而20世纪80年代以来年代际振荡信号减弱,并且太阳总辐射气候态以偏少为主。     

几种水平面太阳总辐射量计算模型的对比分析

利用中国区域1961-1999年39 a间98个常规气象观测数据,建立6个模型分别以天文辐射、干洁大气总辐射和湿洁大气总辐射为起始数据,进行太阳辐射日总量的模拟,对比分析了6个水平面太阳总辐射量计算模型的性能.结果表明:在三种起始数据中,干洁大气总辐射和湿洁大气总辐射均能较好地体现宏观地势对太阳辐射空间分布的影响,以湿洁大气总辐射为起始数据的计算模型拟合精度相对较高.对6个水平面太阳总辐射量计算模型的对比分析发现:2个以日照百分率为主导因子,气温日较差为修正项的综合模型拟合误差最小,精度最高;经典的日照百分率模型次之,但其模型系数最稳定可靠;3个气温日较差模型拟合效果最差.最终选用经验系数稳定、拟合精度较高的日照百分率模型,制作了2001年中国水平面太阳辐射日总量空间分布图.     

安塞黄土丘陵区紫外辐射分布变化特征

利用MILOS520自动气象站观测的安塞黄土丘陵区2005-2008年的紫外辐射、总辐射、日照时数、相对湿度、气温等资料,分析年、月紫外辐射的空间分布特征。结果表明：安塞黄土丘陵区紫外辐射月际分布为：年初、年底辐射量小,4—8月辐射量大;紫外辐射的日变化规律显著,基本上遵循正态分布规律,即呈抛物线型变化,早晚辐射量小、中午前后紫外辐射量大;最大紫外线指数为11．9,紫外辐射强度与总辐射、气温呈正相关,与相对湿度呈反相关。     

北疆天然草场牧草产量分布模型

本文首先建立新疆北部气候要素的垂直分布模型，结果表明，在北疆地区，气温随海拔高度上升而凝减，降水量呈物线分布，在中山带达到最大。然后利用天然草场资源调查资料和相应气象站及推算的资料，建立天然草场牧草产量与气象条件的分布模型，年降水量每增加1毫米，天山北坡中部和西部的天然草场平均单产可增加0．94和0．82公斤，生存气候模型可用于推算天然草场牧草产量空间分布。     

成都市太阳辐射时间变化特征及对气候因子的影响

基于成都市1991至2020 年太阳总辐射、直接辐射、散射辐射、气温、蒸发、日照时数等气象资料,采用线性趋势、Maan-KendaⅡ等方法研究太阳辐射的年、月、日变化特征,以及太阳总辐射的变化对气温、蒸发等气候因子的影响。结果表明：太阳总辐射、直接辐射逐年增多趋势明显,线性倾向率分别为29.69、20.25 MJ·m-2/a;太阳总辐射2010 年出现突变,突变年后较突变年前年平均太阳总辐射增多497.22 MJ·m-2。散射系数呈逐年减小趋势,线性倾向率为每10 年减少0.6。太阳总辐射与气温、蒸发、日照时数呈正相关,均通过显著性检验。太阳总辐射每增加10 MJ·m-2/a,年平均气温升高0.006℃,日照时数增加1.7 h,蒸发量增大1.2 mm。对太阳辐射增加的原因分析,人类活动造成的气溶胶含量减少可能是太阳辐射增加的一个原因。     

辽宁省追踪式与最佳倾角斜面总辐射的推算与分析

利用辽宁省1993—2016年61个气象站的日照百分率逐月数据、6个太阳辐射观测气象站的逐时太阳总辐射数据,采用太阳辐射的气候学计算方法、Klein各向异性散射模型和Hay各向异性散射模型分别推算各站水平面、最佳倾角斜面和追踪式斜面的太阳总辐射的推算值并进行了对比与分析。同时利用1993—2016年日平均总云量数据,得到各站的累年平均晴天日数,并分析辽宁省太阳总辐射空间分布差异的原因。结果表明:全省最佳倾角角度为36°～41°,最小出现在金州,最大分别出现在康平、昌图、法库和西丰;最佳倾角斜面太阳总辐射在辽宁西部和北部地区明显偏多,其中,朝阳北部和阜新西部部分地区最多;追踪式斜面较最佳倾角斜面太阳总辐射的增加量和提升百分比的幅度均较大,分别达到约700～2300 MJ/m2和13%～41%,且存在较明显的呈区域性分布特征,其中,太阳总辐射的增加量在辽宁西部更明显,而太阳总辐射的提升百分比则以沿海地区的幅度更大,超过37%,大连南部更是超过39%;晴天日数或云量是影响辽宁省太阳能总辐射的空间分布差异的主要因素。     

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。     

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.     

Evaluation of support vector machine for estimation of solar radiation from measured meteorological variables

Solar radiation is an essential and important variable to many models. However, it is measured at a very limited number of meteorological stations in the world. Developing method for accurate estimation of solar radiation from measured meteorological variables has been a focus and challenging task. This paper presents the method of solar radiation estimation using support vector machine (SVM). The main objective of this work is to examine the feasibility of SVM and explore its potential in solar radiation estimation. A total of 20 SVM models using different combinations of sunshine ratio, maximum and minimum air temperature, relative humidity, and atmospheric water vapor pressure as input attributes are explored using meteorological data at 15 stations in China. These models significantly outperform the empirical models with an average 14 % higher accuracy. When sunshine duration data are available, model SVM2 using sunshine ratio and air temperature range is proposed. It significantly outperforms the empirical models with an average 26 % higher accuracy. When sunshine duration data are not available, model SVM19 using maximum temperature, minimum temperature and atmospheric water vapor pressure is proposed. It significantly outperforms the temperature-based empirical models with an average of 18 % higher accuracy. The remarkable improvement indicates that the SVM method would be a promising alternative over traditional approaches for estimation of solar radiation at any locations.     

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.     

Models for obtaining daily global solar irradiation from air temperature data

The study presents a critical assessment of the possibility of global solar irradiation computation by using air temperature instead of sunshine duration with the classical Ångström equations. The reason for this approach comes from the fact that, although the air temperature is a worldwide measured meteorological parameter, this is rarely used in solar radiation estimation techniques. More than that, the literature is very silent concerning the testing of such models in Eastern Europe. Two new global solar irradiation models (to be called AEAT) related to solar irradiation under clear sky conditions and having the minimum and maximum daily air temperature as input parameters were tested and compared with others from the literature against data measured at five stations in Romania in the year 2000. The accuracy of AEAT is acceptable and comparable to that of the models which use sunshine duration or cloud amount as input parameters. Since temperature-based Ångström correlations are strongly sensitive to origin, the approach for AEAT as a tool for potential users is presented in detail. Additionally reported is a new method to increase the generality of AEAT concerning the extension of the geographical application area. Based on overall results it was concluded that air temperature successfully substitutes sunshine duration in the estimation of the available solar energy.     

Fuzzy modelling of solar irradiation using air temperature data

Summary Fuzzy sets theory is applied to relate global solar irradiation to both the daily average and the daily amplitude of air temperature. In addition to the presentation of a new mapping technique, from the input to the output of the model, an innovative approach for the tuning of the fuzzy algorithm to fit a local meteo-climate is proposed. Since air temperature-based solar radiation models are strongly dependent on the origin location, the adaptive method presented here is designed as a tool for potential users to either increase the application area or to devise more precise local models. A critical assessment of fuzzy model performances and limitations has been conducted. Results reported here demonstrate the potential of modelling solar irradiation using fuzzy sets approach. Authors’ address: E. Tulcan-Paulescu, M. Paulescu, Physics Department, West University of Timisoara, V. Parvan 4, 300223 Timisoara, Romania.     

基于气象站资料的中国地区太阳日辐射量算法研究

现行计算水平面太阳日辐射主要有两种方式:一种是利用影响辐射的相关要素建立模型,另一种是依据实测资料进行空间插值。但后一种方法若要保证精度则需有足够多的样本。针对上述问题,利用我国不同区域67个站点的数据,在VP-RAD模型的基础上,建立了一个适用于中国地区的逐日太阳辐射算法CNR,该算法仅需要输入站点基本信息、最高最低温度和降水量。模拟结果与实际观测结果比较吻合。     

Estimating solar radiation on tilted surfaces with various orientations: a study case in Karaj (Iran)

Summary The aim of this study is the evaluation of models that estimate daily global solar radiation on tilted surfaces from that measured on horizontal surfaces. Global solar radiation incident on a tilted plane consists of three components: beam radiation, diffuse radiation and reflected radiation from the ground. The Klein (1977) method, modified by Andersen (1980), was used for estimating direct solar radiation incident on tilted surfaces and an isotropic model was used for estimating reflected solar radiation incident on a tilted plane. In contrast models for the diffuse radiation component show major differences, which justifies a validation study which has been done. Eight models for derivation of daily slope diffuse irradiance from daily horizontal diffuse irradiance were tested against recorded slope irradiances at Karaj (35°55′ N; 50°56′ E), Iran. The following models were included: Badescu (2002), Tian et al. (2001), Reindl et al. (1990), Skartveit and Olseth (1986), Koronakis (1986), Steven and Unsworth (1980), Hay (1979) and Liu and Jordan (1962). All the models use the same method for calculating beam radiation as well as ground reflected radiation. However, only diffuse component of radiation was compared. Statistical indices showed that Reindl’s model gives the most accurate prediction for the south-facing surface and Koronakis’s model performs best for the west-facing surface. The Relative Root Mean Square Errors (%RMSE), except for Steven and Unsworth’s model that has unacceptable results, for whole data range from 1.02 to 10.42%. In general, Reindl’s model produces the best agreement with the measured tilted data.     

沪宁高速公路路面温度变化特征及统计模型

使用2006年7月-2007年6月沪宁高速公路沿线梅村和仙人山站附近的逐分钟路面温度、气温、湿度、风向、风速、降水气象资料, 分析了梅村和仙人山不同季节和不同天气状况下路面温度的日变化特征。结果表明:不同季节路面温度和气温具有明显的日变化;日出至日落时段,路面温度与气温有较大差异。在此基础上,应用逐步回归方法建立了梅村和仙人山最高和最低路面温度统计模型, 得出最低路面温度模型模拟结果与实况的变化趋势接近,误差绝对值不超过2℃, 具有很好的实际应用价值; 而最高路面温度模型在一定程度上模拟结果偏差较大,实际应用中需进行适当修订。