基于聚类分区的中国夏季降水预测模型  被引量:14

Summer Precipitation Prediction Models Based on the Clustering Regionalization in China

在线阅读下载全文

作  者:杜良敏[1] 柯宗建[2] 刘长征[2] 肖莺[1] 刘绿柳[2] 

机构地区:[1]武汉区域气候中心,武汉430074 [2]国家气候中心,北京100081

出  处:《气象》2016年第1期89-96,共8页Meteorological Monthly

基  金:公益性行业(气象)科研专项(GYHY201306024;GYHY201306033和GYHY201406022);国家重大科学研究计划(2012CB955902);国家自然科学基金项目(41005051和41205039)共同资助

摘  要:文章基于近邻传播客观聚类方法对中国夏季降水进行了气候分区,以中国不同分区的夏季降水为预测对象,使用前期的海温和海平面气压场为预测因子,利用图像标签算法提取高相关封闭区域的预测因子信息。结合最小二乘回归法建立预测模型。采用Ps评分、距平符号一致率和距平相关系数三种评分方法检验了该预测模型,比较了四种不同的因子配置方案的预测能力。研究结果表明,利用冬春季海温的演变特征结合海平面气压的年际变化为预测因子的分区预测模型效果较好,在1982—2009年期间的平均交叉检验平均Ps得分为81.4,距平符号一致率为63%,距平相关系数为0.35,2010—2014期间的独立样本预测检验的平均评分分别为77.1,58%和0.19,且逐年回报效果较为稳定,表明该方法对中国夏季降水有较好的预测效果。研究结果显示,该预测模型能较好地预测出2014年中国夏季降水南多北少的分布特征。Based on affinity propagation clustering method, summer precipitation is regionalized over China. Summer precipitation in different regions serves as predicted objects, and preceding sea surface tem- perature and sea level pressure are selected to be predictors. By methods of image labeling algorithm, consecutive high correlation areas are extracted to determine the predictors. Least squares regression method is used to construct a model to predict summer precipitation in different regions. Different scoring methods including Ps, the anomaly sign sameness rate and anomaly correlation coefficient are used to validate the skills of prediction model in four different factor combination schemes. The results show that the model performs best when sea surface temperature and sea level pressure in winter and spring are together considered as factors. The averaged Ps score of cross validation is 81.4 from 1982 to 2009, with the anomaly sameness rate 63% and anomaly correlation coefficient 0.35. The retrospective forecast verification shows that the averaged scores from 2010 to 2014 are 77.1, 58% and 0.19, respectively. The reforecast skills are relatively stable every year, which means that the method has a good ability to predict summer precipitation in China. Moreover, it succeeds to predict the spatial characteristic of southern flood and northern drought in China in summer 2014.

关 键 词:近邻传播聚类 分区 夏季降水预测 图形标签算法 

分 类 号:P467[天文地球—大气科学及气象学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象