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四川省不同区域地表太阳总辐射模型适用性评价 被引量:6

Applicability Evaluation of Global Solar Radiation Models in Different Zones of Sichuan Province
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摘要 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(R_(s))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R_(s)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R_(s),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R_(s)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。 The global solar radiation(R_(s)) 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 R_(s) 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 R_(s) 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 R^(2) 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±0.714 MJ·m^(−2)·d^(−1).The hybrid model Chen was the best in zone Ⅱ(MAE was 1.510±0.027 MJ·m^(−2)·d^(−1)) and zone Ⅲ(MAE was1.510±0.027 MJ·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 R_(s) 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.
作者 邹清垚 崔宁博 龚道枝 胡笑涛 姜守政 吴宗俊 何紫玲 ZOU Qing-yao;CUI Ning-bo;GONG Dao-zhi;HU Xiao-tao;JIANG Shou-zheng;WU Zong-jun;HE Zi-ling(State Key Laboratory of Hydraulics and Mountain River Engineering/College of Water Resource and Hydropower,Sichuan University,Chengdu 610065,China;State Key Engineering Laboratory of Crops Efficient Water Use and Drought Mitigation,Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences/Key Laboratory of Dryland Agriculture of Ministry of Agriculture,Beijing 100081;Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas of Ministry of Education,Northwest A&F University,Yangling 712100)
出处 《中国农业气象》 CSCD 北大核心 2021年第7期537-551,共15页 Chinese Journal of Agrometeorology
基金 国家自然科学基金资助项目(51922072,51779161) “十三五”国家重点研发计划项目(2016YFC0400206-03) 中央高校基本科研业务费专项资金资助项目(2017CDLZ-N22,2018CDPZH-10,2019CDPZH-10,2019CDLZ-10)。
关键词 地表太阳总辐射(R_(s))模型 四川省 辐射区 不同天气类型 适用性评价 Global solar radiation(R_(s))models Sichuan province Solar radiation zones Different weather types Applicability evaluation
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