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A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China

机译:中国不同气候典型气象年的混合生成方法

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摘要

Since a representative dataset of the climatological features of a location is important for calculations relating to many fields, such as solar energy system, agriculture, meteorology and architecture, there is a need to investigate the methodology for generating a typical meteorological year (TMY). In this paper, a hybrid method with mixed treatment of selected results from the Danish method, the Festa-Ratto method, and the modified typical meteorological year method is proposed to determine typical meteorological years for 35 locations in six different climatic zones of China (Tropical Zone, Subtropical Zone, Warm Temperate Zone, Mid Temperate Zone, Cold Temperate Zone and Tibetan Plateau Zone). Measured weather data (air dry-bulb temperature, air relative humidity, wind speed, pressure, sunshine duration and global solar radiation), which cover the period of 1994–2015, are obtained and applied in the process of forming TMY. The TMY data and typical solar radiation data are investigated and analyzed in this study. It is found that the results of the hybrid method have better performance in terms of the long-term average measured data during the year than the other investigated methods. Moreover, the Gaussian process regression (GPR) model is recommended to forecast the monthly mean solar radiation using the last 22 years (1994–2015) of measured data.
机译:由于位置的代表性气候数据集对于与许多领域(例如太阳能系统,农业,气象和建筑)有关的计算很重要,因此有必要研究产生典型气象年(TMY)的方法。本文提出了一种混合方法,将丹麦方法,Festa-Ratto方法和改进的典型气象年方法中的部分结果进行混合处理,以确定中国六个不同气候带中35个地点的典型气象年(热带区,亚热带区,温带,中温带,冷温带和青藏高原带)。获得了涵盖1994年至2015年期间的实测气象数据(空气干球温度,空气相对湿度,风速,压力,日照时间和全球太阳辐射),并将其应用于形成TMY的过程中。在这项研究中,对TMY数据和典型的太阳辐射数据进行了调查和分析。结果发现,就年内的长期平均测量数据而言,混合方法的结果比其他调查方法具有更好的性能。此外,建议使用高斯过程回归(GPR)模型,以使用最近22年(1994-2015年)的测量数据来预测月平均太阳辐射。

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