摘要
基于气象要素的品质评价模型(气候品质)较生理生化指标构建的评价体系更简便易行,但目前气候品质模型不确定性较大,精度有待进一步提高。利用2006—2016年奉化和2015—2016年慈溪地区水蜜桃品质因子和气象观测资料,将Monte Carlo法和TS评分(threat score,TS)分析法相结合,构建水蜜桃的气候品质评价模型,以提高对综合品质评估的精度,并利用模型对浙江地区水蜜桃气候品质时空分布特征进行模拟。结果表明:Monte Carlo法可将综合品质评估的不确定性缩小21%(16%~26%);利用TS评分分析法构建的气候品质集合模型的模拟结果与基于品质因子构建的综合品质之间相关系数高达0.97,绝对误差和均方根误差分别为0.01和0.02,较单一模型的模拟精度明显提升;1971—2000年,浙江省水蜜桃品质的气候倾向率为-0.02·10 a-1,21世纪初期气候倾向率达-0.05·10a-1,且年际波动增大;全省水蜜桃气候品质为0.55(0.49~0.63),由沿海向内陆逐步递减。基于Monte Carlo和TS评分分析法构建的水蜜桃气候品质评价模型能较好地模拟浙江地区水蜜桃综合品质,为大范围水蜜桃品质精细化评估提供了有效方法。
The quality evaluation system based on meteorological elements （climate quality） is more convenient and acceptable than that based on physiological and biochemical indices. However, the simulation accuracy of climate quality model needs to be improved. Based on the observational datasets of peach quality and meteorology in Fenghua （2006-2016） and Cixi （2015-2016） in Zhejiang Province, the climate quality of juicy peach was evaluated. The Monte Carlo method and threat score （TS） analysis method were employed to improve the accuracy of the integrated quality evaluation. The spatial and temporal variations of peach quality in Zhejiang were analyzed using the climate quality model. The Monte Carlo method well reduced the uncertainty of integrated quality by 21% （16%-26%）. The prediction accuracy of ensemble model constructed by TS score analysis method was significantly higher than that of a single model. The correlation coefficient between the integrated qualities established by the climatic quality ensemble model and biochemical factors based model was as high as 0.97, with the absolute error and root mean square error being 0.01 and 0.02, respectively. From 1971 to 2000, the climate trend rate of peach quality in Zhejiang Province was -0.02·10 a^-1. In the early 21st century, the climate trend rate reached -0.05·10 a^-1, and the annual fluctuation increased. The climate quality of peaches in Zhejiang Province was 0.55 （0.49-0.63）, decreasing from coastal regions to inland. The climatic quality evaluation model based on Monte Carlo method and TS score analysis can well simulate the integrated quality of juicy peach in Zhejiang Province, providing an effective method for the refined assessment of peach quality at regional scale.
作者
杨栋
金志凤
丁烨毅
黄鹤楼
王治海
YANG Dong;JIN Zhi-fen;DING Ye-yi;HUANG He-lou;WANG Zhi-hai(Ningbo Bureau of Meteorology,Ningbo 315012,Zhejiang,China;Zhejiang Climate Center,Hangzhou 310017,China)
出处
《生态学杂志》
CAS
CSCD
北大核心
2018年第8期2532-2540,共9页
Chinese Journal of Ecology
基金
浙江省重点科技专项(2015C02048)
浙江省气象局2016年重点科技项目(2016ZD10)
宁波市气象局一般项目(NBQX2017004B)资助
