摘要
基于1961-2000年辽宁53个测站40a逐年的月气温距平和月降水距平百分率资料,根据EOF(经验正交函数)展开的空间特征向量分布特征,将前3个主要特征向量时间系数作为预报量,将500hPa高度场的高度距平、地转涡度作为预报因子,利用多元统计回归分析,建立了一套定点、定量预测辽宁各月气温与降水量的数学模型。利用该模型对2001~2005年辽宁53个测站的月气温距平和月降水距平百分率进行逐月预报试验。结果表明:对气温和降水量的趋势预报的评分均比较好,有87%以上的月气温距平预测结果的评分超过66.0分,各月的平均风评分均高于66.0分,年平均为75.5分或以上,总平均为83.1分;有70%的月降水距平百分率预测结果的R评分超过60.0分,各月的平均R评分都高于53.0分,年平均为58.0分以上,总平均为66.5分。但对异常气候的预测效果不明显。
Based on monthly temperature and precipitation anomaly in 53 observation stations from 1961 to 2000 in Liaoning province and multi-regress statistical analysis,a short-term climate forecast model was developed to predict monthly mean temperature and precipitation with three main eigenvectors of spatial characteristics of EOF (Empirical Orthogonal Function) expansion as predictions and 500 hPa height anomaly and geostrophic vorticity as the prediction factors. Monthly temperature and precipitation anomaly percentage were predicted by the model in 53 observation stations of Liaoning. The results showed that trend prediction scores of temperature and precipitation were high. More than 87 96 scores of monthly air temperature anomaly prediction were greater than 66, so did the monthly average Ps scores. The annual average Ps scores of air temperature anomaly predictions were all greater than 75.5 and the total average Ps score was 83.1. Furthermore,70 % Ps scores of anomaly percentage of monthly precipitation prediction were above 60, and the monthly average Ps scores were above 53. The annual average Ps scores of anomaly percentage of precipitation prediction were all greater than 58 and the total average score was 66.5. But the effect of abnormity climate prediction was not obvious.
出处
《气象与环境学报》
2006年第6期11-17,共7页
Journal of Meteorology and Environment
基金
科技部农业科技成果转化资金项目(04EFN217400411)资助
关键词
气温距平
降水距平百分率
EOF展开
短期气候预测
数值预报产品释用
Air temperature anomaly
Anomaly percentage of precipitation
EOF expansion
Short-term climatic forecast
Explanative application of numerical forecasting products