|
|||||
|
|
| 广东降水延伸期预报的探索 | |
| 引用本文： | 谌志刚,王婷,纪忠萍,刘云香,李晓娟.广东降水延伸期预报的探索[J].气象科学,2013,33(3):296-301. |
| 作者姓名： | 谌志刚 王婷 纪忠萍 刘云香 李晓娟 |
| 作者单位： | 1. 广州市气象台,广州,510080 2. 广东省气候中心,广州,510080 3. 广州中心气象台,广州510080;中国气象科学研究院灾害天气国家重点实验室,北京100081 4. 赣州市气象台,江西赣州,344400 5. 广州中心气象台,广州,510080 |
| 基金项目： | 广东省气象局项目(2008A02);广东省气象科技计划项目(200903);公益性行业(气象)科研专项(GYHY201006018);中国气象局气象新技术推广预报员专项(CMATG2007Y04);广东省科技计划项目(2006B37202004);广东省气象局科研课题(2007C01);广东省科技计划项目 |
| 摘 要： | 利用1961-2005年广东省站逐日降水资料,采用奇异谱分析结合自回归模型对广东候平均降水进行未来1～5候的延伸期预报试验.结果表明,广东省降水侯平均存在一个准40 ～60 d的振荡周期,对1961-2000年候降水重构相关系数在0.96以上.对2001-2005年候降水进行未来1～5候的预报试验,预报效果除2003年后延第5候较差外,其它4 a的预报结果都较好.后延第1候预报相关系数最高达到0.86,后延预报到第5候时相关系数也在0.3以上.从预报平均相对均方根误差来看,5 a均在30％以内,预报的稳定性和效果较理想.总体说明奇异谱分析结合自回归模型是一种较为有效的预报方法,在未来10～30 d延伸期天气预报业务中有一定的参考价值. |
| 关 键 词： | 降水延伸期预报 奇异谱分析 自回归模型 |
| 收稿时间： | 1/5/2012 12:00:00 AM |
| 修稿时间： | 2012/7/31 0:00:00 |
Exploration of extended-range forecast of precipitation in Guangdong |
|
| CHEN Zhigang,WANG Ting,JI Zhongping,LIU Yunxiang and LI Xiaojuan.Exploration of extended-range forecast of precipitation in Guangdong[J].Scientia Meteorologica Sinica,2013,33(3):296-301. | |
| Authors: | CHEN Zhigang WANG Ting JI Zhongping LIU Yunxiang and LI Xiaojuan |
| Institution: | Guangzhou Meteorological Observatory, Guangzhou 510080, China;Guangdong Climate Center, Guangzhou 510080, China;Guangzhou Center Meteorological Observatory, Guangzhou 510080, China;National Key Laboratory of Severe Weather of Chinese Meteorological Academy, Beijing 100081, China;Ganzhou Meteorological Observatory, Jiangxi Ganzhou 344400, China;Guangzhou Center Meteorological Observatory, Guangzhou 510080, China |
| Abstract: | A statistical method based on the combination of singular spectrum analysis (SSA) with autoregressive statistical model is applied to reconstruct extended-range forecasts of precipitation from 1961 to 2005 in Guangdong. The results show that the precipitation in Guangdong reveals a 40-60 d circle and the correlation coefficient between reconstruction and observation is above 0.96; the forecast results of the other 4 a are good except the fifth pentad forecast in 2003. The highest correlation coefficient between extended-range forecast and observation of the first pentad is up to 0.86 and the fifth pentad is above 0.3. The average relative mean square errors are smaller than 30% for the 5 a, which means the prediction is of high credibility and stability by using SSA-AR and has reference value in extended-range forecast. |
| Keywords: | Extended-range forecast of precipitation Singular spectrum analysis Autoregressive statistical model |
| 本文献已被 万方数据 等数据库收录！ | |
| 点击此处可从《气象科学》浏览原始摘要信息 | |
| 点击此处可从《气象科学》下载免费的PDF全文 | |