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投稿时间：2013-01-24 修订日期：2013-05-26
投稿时间：2013-01-24 修订日期：2013-05-26
中文摘要: 对华北区域的天气气候学研究，有助于理解该区域大气环流场与地面要素场之间的相互联系。利用自组织神经网络算法（SOMs），基于1958—2002年夏季ERA 40日平均海平面气压距平场（MSLPA），对华北区域的海平面气压场进行分型，研究其天气气候特征。36种典型地面环流形势被识别出来，包括强北高南低、强西高东低槽、强西北低东南高和强东部高压西伸4种极端类型，以及它们之间的过渡型。天气型的空间特征分析表明二维自组织图上天气型的对称性体现了华北区域天气气候的一般性特征，而非对称性则体现其独特性。天气型演变特征分析表明高、低压系统越强，或以高压系统活动为主时，华北地区的天气形势相对稳定，反之则转变较快。年际变化分析指示出其中6种天气型出现较明显的年际线性变化趋势。最后，分析天气型相应的降水分布特征，表明区域内不同地区的降水来自不同天气型的影响，地面环流场的细小差别将会造成地面强降水中心位置的较大不同，且地形的影响将进一步放大该差别。上述分析结果采用更完整和更高时间分辨率的资料，定量化地研究华北区域夏季的天气分型特征，拓展其天气气候学研究。研究成果可用于发展客观化的数值模式典型天气过程识别技术，以及作为区域气候情景分析的基础。
中文关键词: 天气气候学，天气型，降水分布，自组织神经网络，华北区域
Abstract:Analysis of the synoptic climatology over the North China Area promotes a better understanding of the relationships between atmospheric circulation and surface elements. Therefore, investigation on synoptic climatology features is conducted based on the classified synoptic types of North China using the summer ERA 40 MSLP data from 1958 to 2002 which are treated by self organizing maps (SOMs) algorithm. 36 different synoptic patterns are identified, which can be divided into 4 kinds of extreme types such as strong north high and south low, strong west high and east trough, strong northwest low and southeast high and westward extension of strong eastern high, as well as transitional types between them. Study of spatial characteristics indicates that the symmetry of synoptic types in 2D self organizing maps reflects the general characteristics of synoptic climatology over the North China Area, whereas the asymmetry represents the unique features. Study of temporal characteristics shows that synoptic situation of the study area is relatively more stable with stronger high and low systems, or with dominant high system, and vice versa. By referring to the interannual analysis, it is apparent that 6 patterns are dominated by remarkable linear trends. Finally, analysis is performed on precipitation distribution characteristics of the corresponding synoptic patterns. It shows that the rainfall in different parts of North China is contributed by distinct synoptic types, and slight changes in surface circulation can produce drastically different locations of precipitation center, while the topographic effect will further amplify the difference. This study uses a more comprehensive dataset and higher temporal resolution data than most of the past studies to quantitatively investigate the summer synoptic types in North China, resulting in the expansion of synoptic climatology research over the study area. Therefore， results here can be applied to develop the identification technology of the typical weather process in numerical weather predication, and to be the basis of regional climate scenarios research.
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基金项目:国家科技支撑计划项目(2009BAC51B03)和青年科学基金项目(41005031)共同资助
| Author Name | Affiliation |
| DAI Kan | National Meteorological Centre, Beijing 100081 |
| JIN Ronghua | National Meteorological Centre, Beijing 100081 |
| HU Ting | National Climate Centre, Beijing 100081 |
引用文本：
代刊,金荣花,胡婷,2013.基于自组织神经网络算法的华北区域夏季天气气候学特征[J].气象,39(7):801-812.
DAI Kan,JIN Ronghua,HU Ting,2013.Using Self Organizing Maps to Investigate Summer Synoptic Climatology in North China Area[J].Meteor Mon,39(7):801-812.
代刊,金荣花,胡婷,2013.基于自组织神经网络算法的华北区域夏季天气气候学特征[J].气象,39(7):801-812.
DAI Kan,JIN Ronghua,HU Ting,2013.Using Self Organizing Maps to Investigate Summer Synoptic Climatology in North China Area[J].Meteor Mon,39(7):801-812.