建瓯地面太阳总辐射与气象要素的关系研究

Relationship Between Surface Solar Radiation and Meteorological Elements in Jian'ou

以福建省建瓯市2010～2011年两年逐时太阳总辐射和气象要素(气温、相对湿度、云量等9个气象要素)资料为研究对象,首先研究太阳总辐射与各常规气象要素的关系,然后利用2010年总辐射和常规气象要素分季节分早中晚建立预报模型预报201 1年总辐射,最后进行误差分析。结果表明:太阳总辐射与气温、水汽压、相对湿度、云量(低、总)、地温、降水量以及日照有关,其中水汽压、相对湿度、降水量及云量与总辐射负相关,其他呈正相关;与总辐射相关性最小的是风速、其次是水汽压,最大的是日照、其次是地温。分季节分早中晚建立逐步回归方程发现:每日逐时主要贡献因子不尽相同,春季为气温、相对湿度、地温和日照;夏季为地温、日照;秋季为相对湿度、地温和日照;冬季早上总低云量、地温和日照是总辐射的主要贡献因子,中午和傍晚气温、相对湿度、地温和日照是总辐射的主要贡献因子。预报结果发现:预报值与实际值误差较稳定,基本维持在10%～45%之间,夏季误差最小,其次是秋季和春季,冬季的误差最大,中午比早上和傍晚的预报效果好。

Based on the data of solar radiation and normal meteorological elements during 2010--2011 in Jian＇ou, Pujian Province, the relationship between them was analyzed, then a diurnal forecast model was built by using the solar radiation in 2010 and meteorological data. Finally error analysis was carried out. The results are as follows. The solar radiation has a close relationship with temperature, pressure, relative humidity, cloud,surface temperature and duration of sunshine, in which water vapor pressure, relative humidity, precipitation and cloud cover and total exposure are negative correlation, others are positive related. The smallest correlation between normal meteorological elements and total amount of radiation is the wind speed, followed by water vapor pressure, while the biggest one is the sunshine, followed by ground temperature. By using the gradually regression equation established in different seasons and daytime, the hourly and daily contribution factors were found to be different as follows： there are temperatures, relative humidity, ground temperature and solar radiation in spring; ground temperature and sunshine in summer; relative humidity in autumn, winter morning total low cloudiness, ground temperature and sunshine in winter are the main contribution factors to the total irradiation vloume, while the temperature at midday and nightfall, relative humidity, ground temperature and sunshine are main contribution factors to the total irradiation volume. The forecast results indicate that the error between forecast value and actual value are relatively stable, which maintained between 10%-45%. The error value is the smallest in summer, followed by autumn and spring, and the biggest in winter. The forecast effect is better at midday than in the morning and evening.