...
首页> 外文期刊>Solar Energy >A survey on different radiative and cloud schemes for the solar radiation modeling
【24h】

A survey on different radiative and cloud schemes for the solar radiation modeling

机译:太阳辐射建模中不同辐射方案和云方案的调查

获取原文
获取原文并翻译 | 示例
           

摘要

Six different schemes for solar radiation forecasting are presented and validated for three Italian sites with 1 year of solar ground based measurements. The schemes differ for the global (IFS/ECMWF, GFS/NCEP) and local area model (LAMI, RAMS), for the implemented radiative scheme, for the use of an off-line Radiative Transfer Model and also for the cloudiness treatment. The performances of the models have been evaluated not only in clear or cloudy conditions, but in presence of specific types of clouds, detected with the SAFNWC/MSG cloud type software. The influence of local air condition has been confirmed, because of the best results for the site characterized by low levels of aerosols. On average, the relative MAE ranges from 11% to 17% and RMSE from 21% to 28% for the best model when all data have been used. According to the performance evaluation depending on cloudiness, the main errors on forecast occur in presence of very thick clouds, which constitute about the 20% of the cloudy events, but the relative MAE is about 120%. In clear sky conditions the relative MAE is about 5-9% for all the stations and models. A correct interaction between the radiative scheme and the microphysics plays an essential role in the solar forecasting, and the ability to analyze the results in relation to the type of clouds allows you to give an insight into this interaction.
机译:提出了六种不同的太阳辐射预报方案,并针对三个意大利站点进行了一年的太阳地面测量,并对其进行了验证。对于全局模型(IFS / ECMWF,GFS / NCEP)和局部模型(LAMI,RAMS),已实施的辐射方案,使用离线辐射传输模型以及混浊处理,方案都不同。使用SAFNWC / MSG云类型软件检测到的模型的性能不仅在晴朗或多云的条件下,而且在存在特定类型的云的情况下也得到了评估。由于以低水平的气溶胶为特征的站点的最佳结果,已经确认了局部空气条件的影响。平均而言,使用所有数据后,最佳模型的相对MAE范围为11%至17%,RMSE为21%至28%。根据取决于多云的性能评估,预测的主要错误发生在非常厚的云的存在下,约占多云事件的20%,但相对MAE约为120%。在晴朗的天空条件下,所有测站和模型的相对MAE约为5-9%。辐射方案与微观物理学之间的正确相互作用在太阳预报中至关重要,而分析与云类型相关的结果的能力使您可以深入了解这种相互作用。

著录项

  • 来源
    《Solar Energy》 |2013年第ptab期|153-166|共14页
  • 作者单位

    RSE, Environment and Sustainable Development Department, Via Ruhattino 54, Milano, Italy;

    RSE, Environment and Sustainable Development Department, Via Ruhattino 54, Milano, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Solar forecasting; Numerical weather prediction; SAFNWC satellite data;

    机译:太阳预报;数值天气预报;SAFNWC卫星数据;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号