摘要
1996年长江中下游、2002年华中南部以及2006年华南沿海地区出现了显著洪涝,并均伴随强季节内降水活动。在30–60天和10–20天这两个时间尺度上,季节内降水异常均与亚洲季风区大气季节内振荡密切相关。本文选取亚洲季风区大气季节内振荡的关键要素作为预报因子,应用贝叶斯小波频段方案对季节内降水进行了预报时效为15天的延伸期预测。该方案对这三年的季节内降水中心的预测水平均较好,预测与观测的季节内降水相关系数均在0.6以上。
This study utilizes daily Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation(APHRODITE)gridded rainfall and the U.S.National Centers for Environmental PredictionDepartment of Energy reanalysis II products to examine the intraseasonal oscillations(ISOs)of rainfall over Eastern China during each summer of 1996,2002,and 2006.These three cases represent three typical spatial patterns of intraseasonal rainfall anomalies over Eastern China,with the strongest intraseasonal rainfall occurring over the middle and lower Yangtze Basin,southern Yangtze Basin,and Southeast China,respectively.The intraseasonal rainfall anomalies over Eastern China are dominated by both 30–60-and 10–20-day ISOs in each summer and are further modulated by the boreal summer ISOs(BSISOs)over the entire Asian summer monsoon region.The objective of this study is thus to apply the Bayesian wavelet-banding(WB)scheme to predicting intraseasonal rainfall over Eastern China.Several key factors associated with BSISOs are selected as predictors to experimentally develop a 15-day-lead statistical forecast.The forecast results show promise for the intraseasonal rainfall anomalies over Eastern China.Correlations generally greater than or equal to 0.6 are noted between the observed and predicted ISOs of rainfall over the major intraseasonal activity centers during each of the three summers.Such a high forecasting skill on intraseasonal timescales over various areas in Eastern China demonstrates the general usefulness of the WB scheme.
基金
jointly supported by the National Basic Research Program of China[grant numbers 2014CB953902,2012CB417203,and 2012CB955202]
the Priority Research Program of the Chinese Academy of Sciences[grant number XDA11010402]
the National Natural Science Foundation of China[grant numbers 41175059
41375087
and 91537103]