CAJ | 학술논문

利用4个国内外先进的气候模式（国家气候中心、ECMWF、NCEP和JMA）业务预测数据，采用2种多模式集合方法（等权平均和超级集合）、3种降尺度方法（BP-CCA、EOF迭代、高相关回归集成）和3种统计方法（CCA、最优气候值、高相关回归集成）以及降尺度集成和降尺度—统计方法集成，分析了目前季节模式、多模式集合、降尺度、统计方法、降尺度—统计集合等目前常用气候预测技术对新疆夏季降水和冬季气温的业务预测能力。研究表明，以上技术方法对新疆夏季降水和冬季气温的预测能力有较大差别。目前先进的气候业务模式的预测技巧普遍很低，多模式超级集合和降尺度方法的技巧常高于单个模式，并且最佳的降尺度方法通常技巧高于最佳多模式集合方法。同时，统计方法和降尺度方法的预测技巧通常较为接近，而对二者进行超级集合可以具有相对很高的预测技巧。此外，现有常用气候预测技术方法对新疆夏季降水和冬季气温的趋势有一定的预测能力，但对气候异常的空间分布基本无预测能力。建议新疆气候预测技术围绕统计和降尺度方法集合发展。
이용4개국내외선진적기후모식（국가기후중심、ECMWF、NCEP화JMA）업무예측수거，채용2충다모식집합방법（등권평균화초급집합）、3충강척도방법（BP-CCA、EOF질대、고상관회귀집성）화3충통계방법（CCA、최우기후치、고상관회귀집성）이급강척도집성화강척도—통계방법집성，분석료목전계절모식、다모식집합、강척도、통계방법、강척도—통계집합등목전상용기후예측기술대신강하계강수화동계기온적업무예측능력。연구표명，이상기술방법대신강하계강수화동계기온적예측능력유교대차별。목전선진적기후업무모식적예측기교보편흔저，다모식초급집합화강척도방법적기교상고우단개모식，병차최가적강척도방법통상기교고우최가다모식집합방법。동시，통계방법화강척도방법적예측기교통상교위접근，이대이자진행초급집합가이구유상대흔고적예측기교。차외，현유상용기후예측기술방법대신강하계강수화동계기온적추세유일정적예측능력，단대기후이상적공간분포기본무예측능력。건의신강기후예측기술위요통계화강척도방법집합발전。
The operational prediction ability of summer precipitation and winter temperature over Xinjiang is studied with the common techniques including seasonal models,multi-model ensemble, statistical downscaling,statistical methods,ensemble of both downscaling and statistical methods. The operational seasonal models from National Climate Center,ECMWF,NCEP,JMA,two muliti-model ensemble methods (the average and super-ensemble), three downscaling methods (BP-CCA,EOF-ITE,HCRE)and three statistical methods (BP-CCA,OCN,HCRE)used in National Climate Center are employed in this paper. <br> Our study shows that the above techniques and methods have much different prediction abilities on the summer precipitation and winter temperature over Xinjiang. The skill scores of the leading operational seasonal models are very low. Meanwhile, the super-ensemble of models and downscaling methods are often better than single model while the best downscaling method shows higher score than the best multi-model ensemble method. Besides,the skills of statistical methods are similar to the downscaling ones. The super-ensemble of both downscaling and statistical methods often holds quite higher prediction accuracy. What is more, it is indicated that the common methods used in present operation are of certain ability on the prediction of the trend but of few ability on the spatial distribution of the climate anomalies over Xinjiang. It is suggested that the technique on seasonal prediction over Xinjiang should be developed focusing on the ensemble of statistical and downscaling methods.