| 东亚夏季风强度的多尺度统计预测模型 |
| |
| 引用本文： | 纪忠萍,谷德军,林爱兰.东亚夏季风强度的多尺度统计预测模型[J].大气科学,2016,40(2):227-242. |
| |
| 作者姓名： | 纪忠萍 谷德军 林爱兰 |
| |
| 作者单位： | 1.广东省气象台, 广州 510080 |
| |
| 基金项目： | 全球变化研究国家重大科学研究计划2010CB950304、2014CB953901,广东省自然科学基金S2013010016751,国家自然科学基金项目41375095、41175071,中国科学院战略性先导科技专项XDA11010403 |
| |
| 摘 要： | 东亚夏季风强度的变化与中国雨带和旱涝分布密切相关。为了做好东亚夏季风强度的短期气候预测,采用小波分析、Lanczos滤波器、交叉检验等方法,研究了东亚夏季风强度的多尺度变化特征,在年际与年代际尺度上分别寻找了它在前冬海温场、200 hPa纬向风场上的前兆信号,并利用最优子集回归建立了东亚夏季风强度的多尺度统计物理预测模型。结果表明:东亚夏季风强度存在准4年、准13年和准43年的周期振荡。年际尺度上,前冬赤道东太平洋(10°N~10°S,160°W~80°W)海温与东亚夏季风强度有最强的显著负相关,且它与东亚夏季风强度在200 hPa纬向风场上的前兆信号有较强的负相关;年代际尺度上,南半球60°S与35°S附近200 hPa纬向风之差与东亚夏季风强度有最强的显著正相关,且它与东亚夏季风强度在热带印度洋、低纬度东南太平洋、低纬度南大西洋的海温及亚洲副热带200 hPa纬向风等前兆信号有强的正相关。通过探讨这两个前兆因子对东亚夏季风强度的预测意义,揭示了他们影响东亚夏季风强度年际和年代际变化的可能物理过程。所建立的东亚夏季风强度多尺度最优子集回归预测模型,不仅对东亚夏季风强度的年际变化具有较好的预测能力,而且对异常极值年份也具有一定的预测能力。
|
| 关 键 词： | 东亚夏季风强度 前兆信号 多尺度最优子集回归 交叉检验 |
| 收稿时间： | 2014/9/24 0:00:00 |
A Multiscale Statistical Prediction Model of East Asian Summer Monsoon Intensity |
| |
| JI Zhongping,GU Dejun and LIN Ailan.A Multiscale Statistical Prediction Model of East Asian Summer Monsoon Intensity[J].Chinese Journal of Atmospheric Sciences,2016,40(2):227-242. |
| |
| Authors: | JI Zhongping GU Dejun and LIN Ailan |
| |
| Institution: | 1.Guangdong Meteorological Observatory, Guangzhou 5100802.Guangzhou Institute of Tropical and Marine Meteorology, China Meteorological Administration;Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Guangzhou 510080 |
| |
| Abstract: | The intensity of the East Asian Summer Monsoon(EASM) has a close relationship with the distribution of rain bands and drought-flood patterns over China.To better do short-term climate prediction of EASM intensity, its multiscale variation characteristics and relationship with SST and 200 hPa zonal wind at interannual and interdecadal scales were studied using the wavelet transform method, Lanczos filter, and cross-validation.Subsequently, a multiscale statistical physical prediction model for EASM intensity, based on precursor signals, was constructed using the method of optimal subset regression.The results showed that EASM intensity exhibits quasi 4-, 13- and 43-year periodic oscillations. At the interannual scale, the SST in the eastern equatorial Pacific(10°N-10°S, 160°W-80°W) during the previous winter shows the largest significant negative correlation with EASM intensity, and has larger significant negative correlation with precursor signals in the 200 hPa zonal wind field.At interdecadal scales, the difference in 200 hPa zonal wind between approximately 60°S and 35°S has the largest significant positive correlation with EASM intensity.It also has larger significant positive correlation with precursor signals in the SST and 200 hPa zonal wind field, which includes the SST over the tropical Indian Ocean, low-latitude southeastern Pacific, and low-latitude southern Atlantic Ocean, and the 200 hPa zonal wind over the Asian subtropics.The potential of the two above-mentioned precursory factors in predicting EASM intensity was discussed, and the possible physical processes linking the EASM intensity and the two precursory factors at interannual and interdecadal scales explored.The multiscale optimal subset regression prediction model for EASM intensity was constructed with these precursor factors.The model not only showed better prediction ability for the interannual variation of EASM intensity, but also demonstrated certain predictive capability for extreme years. |
| |
| Keywords: | East Asian Summer Monsoon(EASM) intensity Precursor signal Multiscale optimal subset regression Cross-validation |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《大气科学》浏览原始摘要信息 |
| 点击此处可从《大气科学》下载免费的PDF全文 |
|
