首页> 外文会议>International Conference on Solar Energy for Buildings and Industry >Evaluation of NCEP Products (NCEP-NCAR, NCEP-DOE, NCEP-FNL, NCEP-GFS) of Solar Radiation for Karachi, Pakistan
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Evaluation of NCEP Products (NCEP-NCAR, NCEP-DOE, NCEP-FNL, NCEP-GFS) of Solar Radiation for Karachi, Pakistan

机译:Karachi,巴基斯坦太阳辐射的NCEP产品(NCEP-NCAR,NCEP-DOE,NCEP-FNL,NCEP-GFS)的评价

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The solar radiation data measured by ESMAP for Karachi, Pakistan is compared with four NCEP products (NCEP - NCAR, NCEP-DOE, NCEP FNL, NCEP-GFS). The evaluation of satellite estimates of solar radiation against surface measured data is performed on the basis of statistical analysis and daily mean time series. The statistical analysis shows that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for four datasets range from -4.48 to 63.24 W/m~2, 55.70 to 108.77 W/m~2 and 0.966 to 0.976 respectively. The monthly analysis of solar radiation is performed on the basis of daily mean time series to assess the impact of season on their accuracy. Cloud fraction is the main reason for less accuracy of solar radiation products for July and August because of Monsoon in Pakistan. Three-months evaluation of NCEP-FNL is also performed on the basis of monthly mean time series and scatter plots to assess the model performance of dataset in different seasons. The estimates from NCEP-NCAR are least accurate among all datasets whereas the performance of NCEP-FNL is most accurate for initial assessment of solar for Karachi. The results of NCEP-GFS are closer to NCEP-FNL, hence NCEP-GFS can be used to forecast solar energy for Karachi.
机译:通过ESMAP测量的帕拉克,巴基斯坦测量的太阳辐射数据与四个NCEP产品(NCEP - NCAR,NCEP-DOE,NCEP FNL,NCEP-GFS)进行了比较。基于统计分析和每日平均时间序列,执行对表面测量数据的太阳辐射卫星估计的评估。统计分析表明,四个数据集的平均偏置误差(MBE),均方根误差(RMSE)和相关系数(R)从-4.48到63.24 w / m〜2,55.70至108.77 w / m〜2和0.966分别为0.976。在日常平均时间序列的基础上进行太阳辐射的每月分析,以评估季节对其准确性的影响。云分数是7月和八月的太阳辐射产品的准确性,因为巴基斯坦的季风较低。对NCEP-FNL的三个月评估也是根据月平均时间序列和散点图进行的,以评估不同季节数据集的模型性能。 NCEP-NCAR的估计在所有数据集中最准确,而NCEP-FNL的性能最准确地对卡拉奇的初始评估太阳能。 NCEP-GFS的结果更接近NCEP-FNL,因此NCEP-GFS可用于预测卡拉奇的太阳能。

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