CAJ | 학술논문

利用1957-2006年辽宁地区夏季23个站极端最高气温资料和国家气候中心气候监测室的74项环流特征量资料，应用EOF方法对高温极值样本进行分解，研究辽宁极端高温的时空分布规律。结果表明：第一特征向量表现为区域整体一致的特征，中心区位于辽西北、辽北，第二、三特征向量空间分布表现为东西部反位相和南北反位相的特征。普查前3个时间系数与前期环流指数的相关关系，认为前3个时间系数的显著影响因子是不同的。采用CSC准则确定最优预测因子，分别建立各时间系数的回归统计模型，并对高温极值历史拟合序列进行回报检验和预测检验。回报结果表明，各站历史拟合率均保持在一定水平，但拟合率在辽西地区较差。各年历史拟合率极不均衡，多数年份较为稳定，但个别年份拟合率较低。未来3a试验性预测效果逐年下降，模型对未来1a预测能力较好，可以作为业务预测的参考。
이용1957-2006년료녕지구하계23개참겁단최고기온자료화국가기후중심기후감측실적74항배류특정량자료，응용EOF방법대고온겁치양본진행분해，연구료녕겁단고온적시공분포규률。결과표명：제일특정향량표현위구역정체일치적특정，중심구위우료서북、료북，제이、삼특정향량공간분포표현위동서부반위상화남북반위상적특정。보사전3개시간계수여전기배류지수적상관관계，인위전3개시간계수적현저영향인자시불동적。채용CSC준칙학정최우예측인자，분별건립각시간계수적회귀통계모형，병대고온겁치역사의합서렬진행회보검험화예측검험。회보결과표명，각참역사의합솔균보지재일정수평，단의합솔재료서지구교차。각년역사의합솔겁불균형，다수년빈교위은정，단개별년빈의합솔교저。미래3a시험성예측효과축년하강，모형대미래1a예측능력교호，가이작위업무예측적삼고。
Based on the summer extreme high temperature data from the 23 weather stations in Liaoning province and 74 circulation indices information from the climate monitoring department of the National Climate Center ( NCC), China Meteorological Administration ( CMA), the temporal and spatial distribution features of summer ex- treme high temperature in Liaoning province were analyzed by a Empirical Orthogonal Function(EOF) decomposi- tion method. The results show that the ftrst EOF vector is characterized by a uniform anomaly over the whole area and the centers are in the northern and northwestern Liaoning province, while the second and third EOF vectors are the reversed phase patterns in the east and west areas and in the south and north areas, respectively. The correlation coefficient between first three time coefficient series and preceding circulation indices are calculated. It is found that the influencing factors are different for the three time coefficients. The optimum subset regressions are chosen as prediction equations using a CSC evaluation method and the fitting rate of past records in the 23 weather stations and each year are tested. It shows that the fitting rate of past records in the 23 weather stations is generally stable, except for in the western Liaoning province. In addition, the fitting rate is unbalanced each year, and it is stable in most years, while it is low in few individual years. While the prediction effect is good for the first year in the future it declines yearly in the following two years. The results can be used as references in climatic prediction.