四川省不同区域地表太阳总辐射模型适用性评价

选用1994−2016年四川省7个辐射站气象数据，在3个辐射区（川西高原I区、川东盆地II区和川西南山地III区）中评价了6种地表太阳总辐射（Rs）估算模型在3种天气类型（晴、多云、阴）下的适用性，并分析基于天气类型的组合模型在不同区域的模拟效果，以探寻最适宜全省不同区域的Rs估算方法。结果表明：（1）各经验模型在四川省整体表现良好（决定系数R2介于0.554～0.934，P <0. 001），I区（甘孜和红原站）模拟效果最好的为日照时数模型A−P（平均绝对误差MAE为2.210±0.714MJ∙m⁻²∙d⁻¹），II区（成都、绵阳和泸州站）、III区（峨眉山和攀枝花站）模拟效果最佳的均为混合模型Chen（II区MAE为1.510±0.027MJ∙m⁻²∙d⁻¹，III区为1.930±0.006MJ∙m⁻²∙d⁻¹）；（2）6个模型在四川省3种天气类型下的模拟效果呈晴天>多云>阴天的规律，日照时数模型（A−P和Ba模型）能更好地模拟晴天时的Rs，混合模型（Chen和Ab模型）则在多云和阴天时模拟效果更佳，I区在晴天、多云、阴天3种天气下模拟效果最好的模型分别是A−P（整体评价指标GPI为0.850）、Ab（1.294）、Ba（0.862），II区分别为A−P（0.381）、Chen（1.358）、Chen（1.742），III区分别为Chen（0.204）、Chen（0.857）、Chen（0.526）；（3）基于天气类型的组合模型（M新）模拟各区Rs的效果均比未组合前各模型的效果好（3个区GPI分别为0.558、0.582、0.134）。因此，推荐使用基于天气类型的组合模型来估算四川省Rs。

Applicability Evaluation of Global Solar Radiation Models in Different Zones of Sichuan Province

The global solar radiation(Rs) is of great significance in the fields of agricultural production system, hydrometeorological research and clean energy development. Due to the complicated topography and various climate in Sichuan province, the distribution of global solar radiation is uneven. In order to explore the most suitable Rs estimation models for different zones of Sichuan, Sichuan was divided into three solar radiation zones in this paper (zone I: western Sichuan plateau, zone II: eastern Sichuan basin, and zone III: southwest Sichuan mountain) for research. Zone I(Ganzi and Hongyuan stations) has low temperature, sufficient sunshine and strong solar radiation; zone II(Chengdu, Mianyang and Luzhou stations) has high relative humidity, short sunshine duration and low radiation; zone III(Emeishan and Panzhihua stations) is abundant in solar radiation resources, but the air temperature and humidity vary greatly within the zone. In three solar radiation zones, based on the meteorological data from 1994 to 2016, the applicability of six Rs estimation models were evaluated under three weather types(sunny, partially cloudy and cloudy), and the simulation effect of combined models based on weather types in different zones were analyzed. The results showed that:(1) the empirical models performed well in Sichuan province(the coefficient of determination R2 ranged from 0.554 to 0.934, P<0.001). The most accurate simulation model in zone I was sunshine-based model A−P with mean absolute error(MAE) 2.210±0.714MJ∙m⁻²∙d⁻¹. The hybrid model Chen was the best in zone II(MAE was 1.510±0.027MJ∙m⁻²∙d⁻¹) and zone III(MAE was 1.510±0.027MJ∙m⁻²∙d⁻¹). (2) The statistical performance of the six models under three weather types in Sichuan showed sunny>partially cloudy>cloudy. The sunshine-based models(A−P and Ba models) could better simulate the Rs in sunny days, while the hybrid models(Chen and Ab models) had higher accuracy in simulating partially cloudy and cloudy days. The A−P(the global performance indicator GPI = 0.850), Ab(1.294) and Ba(0.862) models were the best models to simulate Rs of zone I in sunny, partially cloudy and cloudy, respectively. The A−P(GPI = 0.381), Chen(1.358) and Chen(1.742) models were the best models to simulate Rs of zone II under three weather types, respectively. The Chen model was the best model to simulate Rs of zone III in sunny, partially cloudy and cloudy with GPI 0.204, 0.857 and 0.526, respectively. (3) The Rs combined models(Mnew) based on weather types had the best simulation accuracy in each zone(GPI were 0.558, 0.582 and 0.134 in 3 zones, respectively). Therefore, it is recommended to use the Rs combined models based on weather types to estimate Rs in Sichuan province.