我国太阳日总辐射计算方法的研究

对全国23个站点的日照时数、日最高气温、日最低气温、太阳日总辐射量等气象要素实测资料进行统计分析,利用回归分析法建立了以日照百分率和气温日较差为主要相关因子的各地日总辐射估算模型。结果表明：除了高原站拉萨以外,推算模型的复相关系数均介于0．80～0．93之间,拟合效果较好。在春、夏季使用独立的季节模型有一定的必要性,该方法适用于我国各地太阳日总辐射的推算,     

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。     

不同数学模型在降水量资料序列订正中适用性探讨

采用逐步多元线性回归模型、一元线性回归模型、综合法模型和比值法模型对分布于全国31个台站的降水量资料进行了模型订正效果的试验与分析。结果表明:（1）逐步多元线性回归模型对年降水量序列的订正效果较好,其相对拟合误差总平均在0.08以下,而其它3种模型与月降水量序列的订正效果较差,相对拟合误差总平均在0.11以上;（2）若将年降水量序列相对拟合误差控制在0.10以内,则要求确定订正方程式的平行资料年数为10年或以上,要求订正站与基本站序列的相关系数在0.85以上;（3）较湿润地区拟合误差较小,反之较大。     

上甸子大气本底站太阳辐射观测数据的质量评价

采用了基准地面辐射观测网络(BSRN)推荐的辐射观测数据质量评价方法,对2005年上甸子大气本底站太阳辐射观测数据进行了质量评价,并通过分析晴空地面太阳总辐射观测值与计算值之间的均方根误差和变差系数来替换BSRN质量评价方法中的"辐射观测值序列的目视"检验步骤.结果表明,通过前3步检验的直接、散射和地面太阳总辐射数据的百分比,除7月和8月外其他月份均在95%以上;地面向上辐射除3、4、7、8和11月在74.7%～85.5%之间外,其他月份均在91%以上.通过前3步检验的晴空地面太阳总辐射观测值与计算值之间的均方根误差均在23.5 W·m-2以下,除11月和12月外其他月份的变差系数均在0.05以下.     

黄淮地区辐射模型适用性评价及参数优化

利用1961—2015年黄淮地区8个辐射站太阳辐射和日照时数等常规气象资料,分别评价6种常用的太阳总辐射和有效辐射估算模型在黄淮地区的适用性,同时采用多元回归分析和迭代等方法,对辐射参数进行优化调整,建立了适合本地区的辐射最优化估算模型。结果表明:童宏良公式和邓根云公式分别在估算太阳总辐射和地面有效辐射时的误差最小,相比其余的辐射估算模型,两者在黄淮地区适用性最好。另外太阳总辐射本地化修正模型的相对误差绝对值(value of Absolute Relative Error, ARE)和均方根误差(Root Mean Squared Error, RMSE)分别为16.28%和1.730 MJ·m~(-2)·d~(-1),优于童宏良公式等常用太阳辐射估算模型;有效辐射本地化修正模型的ARE和RMSE分别为23.19%和1.404 MJ·m~(-2)·d~(-1),优于邓根云公式等常用有效辐射估算模型;因此黄淮地区本地化辐射修正模型适用于当地地表净辐射估算,且具有较好的估算精度。     

基于WRF模式输出统计的逐时太阳总辐射预报初探

基于WRF(weather research and forecasting model)模式逐时输出结果,设计了逐时太阳总辐射的模式输出统计(model output statistics,MOS)预报流程。主要包括:对逐时观测序列进行低通滤波再除以天文辐射,对模式输出因子的筛选和降维,以及建立MOS预报方程,并对2009年1月、4月、8月和10月武汉站逐时太阳总辐射进行预报试验。结果表明,该方案在各月预报相对稳定,拟合和预报效果均较为理想,可使平均绝对百分比误差控制在20%～30%,相对均方根误差控制在30%～40%,相对模式直接预报辐射改进了50%左右。由此可见,通过对模式输出进行解释应用,可以有效提高辐射预报的准确率。此外,客观分析所得的气温、云量、露点、比湿、相对湿度、地面气压等13个模式输出因子可以作为各地区建立MOS辐射预报方程的参考因子。     

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.     

不同天气条件下地基微波辐射计探测性能比对

利用探空数据和毫米波云雷达数据,对在大气探测试验基地同址观测的国内外3种型号地基微波辐射计进行1年（2016年10月—2017年9月）的比对分析,重点分析不同型号地基微波辐射计在晴空和云天下温、湿观测性能特征。结果表明:3种型号地基微波辐射计温度与探空相关系数均超过0.98,达到0.01显著性水平;晴空条件下,德国及国产地基微波辐射计温度平均误差均在±1℃以内（前者为负偏差,后者为正偏差）,误差较小,美国地基微波辐射计系统偏差约为-1.8℃;3种型号地基微波辐射计均方根误差随高度递增,整体均方根误差以德国地基微波辐射计2.2℃为最小,美国地基微波辐射计3.8℃为最大;在有云条件下,3种型号地基微波辐射计平均误差分布较晴空条件下无明显变化,均方根误差较晴空条件有约增加0.5℃。3种型号地基微波辐射计均呈晴空相对湿度误差小于云天误差,低空误差小于中高空误差的特点;晴空条件下,美国与国产地基微波辐射计相对湿度均方根误差分别为15%和18%左右,小于德国地基微波辐射计;云天条件下3种型号微波辐射计均方根误差均较大（26%左右）。     

太阳辐射经验系数插值方法的比较

利用江苏省南京、吕泗、淮安3个日射站以及周边省市共10个日射站逐月日照百分率资料和太阳总辐射资料,利用最小二乘法拟合经验系数a、b,并利用除南京、吕泗2个日射站以外的8个日射站的经验系数a、b,采用多种插值方法计算江苏省70个站的经验系数a、b,并据此求出70个站点逐月太阳总辐射值并分析其分布特征。结果表明：采用反距离权重插值法得到的经验系数a、b,误差最小。结论可为求解江苏省各地太阳总辐射提供科学参考。     

香港地区加权平均温度特征分析

利用香港Kings Park探空站(站号45004)2003—2009年探空资料回归了大气加权平均温度Tm、地面温度Ts、气压es和水汽压Ps的线性公式.通过比较分析发现Tm Ts单因素回归结果和Tm Ts、es、Ps多因素回归结果没有显著差异,但基于本地化探空数据的回归公式精度比Bevis公式高;增加样本数回归分析并不能显著提高公式精度,采用最近一月探空数据回归公式即可很好地由Ts拟合下年Tm,拟合均方根误差(F RMS)为1946 K;用2003年数据回归出的经验公式Tm=11329+05 863Ts去拟合2004—2009年的数据,拟合均方根误差〖JP2〗基本没有差异,因此某地Tm Ts经验公式一次回归可长期使用．通过对全国83个国际交换站2009年探空数据回归得出我国大陆地区最新Tm Ts经验公式为Tm=〖JP〗53244+0783Ts,该一般公式拟合均方根误差与本站数据回归剩余均方根误差(RRMS)相当,可代替本地公式广泛使用．     

A practical model to estimate photosynthetically active radiation using general meteorological elements in a temperate humid area and comparison among models

Although accurately evaluating photosynthetically active radiation is important, much effort is required to measure this radiation using a quantum sensor. We develop a new model that makes estimates using only general meteorological data—solar radiation, atmospheric pressure, air temperature, and relative humidity. Root mean square deviations for eight datasets at five sites in Japan were smaller than 5.2 %, similar to error in other studies and to individual differences of quantum sensors. Most root mean square deviations of nine previous models and our eight datasets are larger than that of the new estimation model, which performed well. This suggests that the model is useful for estimating photosynthetically active radiation in a temperate, humid area of Japan.     

Interpolating methods for solar radiation in Uganda

Summary Existing literature lacks information on evaluation of interpolation methods for the estimation of solar radiation in the East African region. It follows that this study investigates the performance of five interpolations in Uganda which include: Nearest Point, Moving Average, Moving Surface, Trend Surface and Ordinary Kriging. Results have shown that the Moving Average linear decrease is the most appropriate for interpolation of solar radiation in Uganda and subsequent drawing of solar maps. The corresponding normalized mean bias error and root mean square error is 0.035 and 0.078, respectively. The worst performing is the Nearest Point interpolation with normalized mean bias error and root mean square error of 0.084 and 0.149, respectively.     

Analysis of 40 year records of solar radiation data in Shanghai,Nanjing and Hangzhou in Eastern China

Summary In this paper, we analyze global, direct and diffuse solar radiation data on a horizontal surface observed at stations in Shanghai, Nanjing and Hangzhou for the period of 1961 to 2000. The data include monthly averages of the daily clearness index (G/G₀: the ratio of global to extraterrestrial solar radiation) and the diffuse fraction (D/G: the ratio of diffuse to global solar radiation. The present study has processed and analyzed the data, including variables or statistics of mean, and annual monthly and daily total, the diurnal variation and the frequency of daily totals of global solar radiation. A correlation between daily values of clearness index and diffuse fraction is obtained and recommended correlation equations were calculated. The annual variations and trend of yearly series are analyzed for daily global, direct and diffuse radiation on a horizontal surface, as well as for daily clearness index and diffuse fraction in Shanghai, Nanjing and Hangzhou. The results show: 1) the east China is characterized by a decrease in global and direct radiation and a little increase in diffuse radiation and a negative linear relationship was obtained between clearness index and diffuse fraction. 2) The annual variations of global, direct and diffuse radiation for Shanghai, Nanjing and Hangzhou are similar with relative low values of global and direct radiation in June due to the Meiyu period. 3) The acceleration of air pollution and decrease of relative sunshine are the possible causes for the decrease of global and direct radiation.     

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.     

重庆山地区域气象要素空间插值方法对比

利用重庆地区1999年和2018年气象数据, 分别采用薄盘光滑样条、协同克里金、普通克里金、反距离加权4种方法, 从年和月两种尺度对气温、降水、太阳总辐射三个要素进行空间插值; 采取交叉验证方法, 用MAE、MRE、RMSE评估插值精度, 确定各要素最优插值方法。结果表明: 气温和太阳总辐射最优插值方法为薄盘光滑样条, 降水为反距离加权; 插值精度上气温、太阳总辐射高值月份优于低值月份, 降水则相反, 但三个要素均表现出年尺度优于月尺度。MRE检验表明, 插值精度为气温>太阳总辐射>降水, 1999年年尺度插值精度分别为1.86%、4.60%、6.87%, 月尺度插值精度分别为2.79%、5.82%、17.42%;2018年太阳总辐射年、月尺度插值精度分别为3.03%、4.88%, 区域站加密后气温、降水年尺度插值精度分别为2.03%、11.20%, 月尺度对应插值精度分别为3.20%、23.14%。     

塔克拉玛干沙漠腹地逐日太阳总辐射模拟计算 -以达理雅博依绿洲为例

基于塔克拉玛干沙漠腹地面积最大的天然孤立绿洲达理雅博依2015年1月—2016年2月太阳总辐射观测资料,运用H.L.Penman经验公式模拟计算了该地区2015年逐日总辐射累计量,模拟值与实测值的误差分析显示:本气候学方法成功模拟了沙漠腹地总辐射的年内变化趋势。使用模拟值估算得到达理雅博依绿洲2015年太阳总辐射累计量约为5 332.23 MJ·m-2。又以相同方法模拟了塔中气象站2015年3—5月总辐射变化,结果较达理雅博依的模拟更接近实测值,说明本模拟在塔克拉玛干沙漠腹地不同地点结果有效。     

拉萨紫外辐射特征分析及估算公式的建立

本文利用2005~2010年的辐射观测资料对拉萨地区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,结果表明,紫外辐射与太阳总辐射的变化规律基本一致,日变化表现为正午大、早晚小;季变化特征是夏季6月最大,冬季1月最小.紫外辐射日累积值6年平均为0.87 MJ·m-2·d-1;紫外辐射有逐年递减的趋势.紫外辐射与总辐射比值也存在着明显日变化,表现为正午大、早晚小的规律;其季节变化也是夏季最大,冬季最小.紫外辐射与总辐射比值6年平均为0.0418;紫外辐射与总辐射比值也呈现逐年递减的趋势.利用2010年大气质量数和晴空指数,建立了适合于拉萨紫外辐射估量的公式,估算值的瞬时值与观测值的平均相对误差最大为8.66%,紫外辐射日累积重构值与观测值平均相对误差仅为5.5%.     

Assessing the performance of global solar radiation empirical formulations in Kampala, Uganda

Summary Solar radiation incident on the Earth’s surface is a determining factor of climate on Earth, hence having a proper solar radiation database is crucial in understanding climate processes in the Earth’s atmosphere. Solar radiation data may be used in the development of insolation maps, analysis of crop growth and in the simulation of solar systems. Unfortunately, measured solar radiation data may not be available in locations where it is most needed. An alternative to obtaining observed data is to estimate it using an appropriate solar radiation model. The purpose of this study is to assess the performance of thirteen global solar radiation empirical formulations, in Kampala, Uganda, located in an African Equatorial region. The best performing formulations were determined using the ranking method. The mean bias error, root mean square error and t-statistic value were calculated and utilized in the ranking process. Results have shown that the formulation: is ranked the highest and therefore is the recommended empirical equation for the estimation of the monthly mean global solar irradiation in Kampala, Uganda and in other African Equatorial locations with similar climate and terrain.     

Variations and trends in global solar radiation for Turkey

Summary Since measured solar radiation data in Turkey have rather high random errors, sunshine duration data covering the period from 1960 through 1994 from 34 stations in Turkey were taken to derive estimates of monthly mean global solar radiation by a quadratic correlation. The least square linear regression method was applied for trend analysis. Significant negative trends of the annual means were observed with 71 percent of the stations A 3.44 percent decrease in global solar radiation was observed over the last 35 years in Turkey. The decrease in solar radiation is an indication of increased air pollution, as statistical parameters show that Turkey is rapidly expanding economically, and thus air quality has deteriorated correspondingly.With 3 Figures