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气象:2019,45(8):1037-1051
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我国中东部平原地区临界气温条件下降水相态判别分析
陈双,谌芸,何立富,郭云谦
(国家气象中心,北京 100081)
Discrimination Analysis of Snow and Rain Occurring Under Critical Temperature Conditions in Central and Eastern China
CHEN Shuang,CHEN Yun,HE Lifu,GUO Yunqian
(National Meteorological Centre, Beijing 100081)
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投稿时间:2018-09-28    修订日期:2019-01-30
中文摘要: 基于2001—2013年地面观测和探空资料,对地面气温位于0~2℃(以下称临界气温)我国降雪的时空分布及其与降雨的垂直热力特征进行了研究,引入了决策树判别方法对上述条件下雪和雨进行了判别分析,结果表明:临界气温下降雪出现频率总体高于降雨、雨夹雪出现频率,且在我国华北南部至江南北部的中东部地区分布较多,年均可达7.69~15.38站次;临界气温下,降水相态为雨或雪对应的平均温度廓线最大差异位于650 hPa附近,且地面气温较低时,平均温度差异更明显,平均湿度廓线差异则主要位于低层,且在地面气温较高时,平均湿度差异更明显;临界气温下,降水相态为雨时,地面上空存在暖层样本占比,较降水相态为雪时更高,且降雨时暖层主要位于中层,降雪时暖层则主要位于低层,降雨时其暖层强度显著大于降雪时暖层强度;在临界气温下雨雪判别分析中,地面气温能显著提升判别准确率,湿球温度能在一定程度上提升判别准确率,基于云顶温度、中层融化参数、低层湿球温度构建的决策树判别模型,判别准确率达到91.86%,能较好地解决临界气温下雨和雪的判别问题。
Abstract:Based on surface observation and sounding data from 2001 to 2013, the spatial and temporal distribution of snowfall occurring at surface air temperature of 0-2℃ (hereinafter referred to as critical surface temperature condition) in China is analyzed, and comparative analysis of vertical thermal characteristics is made between snow and rain under the above condition, then a decision tree discriminant method is introduced to discriminate snow from rain. The results show that the frequency of snow under the critical surface air temperature conditions is generally higher than that of rain and sleet, and it mainly distributes in the central and eastern regions between southern North China and northern Jiangnan Area, with an average annual number of 7.69-15.38 stations. Combined soundings of snow and rain show maximum temperature difference around 650 hPa, more obvious when T2 m (surface air temperature) is lower. Maximum humidity difference lies around the surface, more obvious when T2 m is higher. A melting layer above the surface exists more frequently in rain than in snow. The melting layer of rain is mainly located in the middle layer, while that of snow is mainly near 1000 hPa. Discriminative accuracies of different decision tree discriminant models constructed from different factors vary differently. T2 m is especially important, and wet bulb temperature can improve the discriminative accuracy in the process of discrimination. The accuracy of the decision tree discriminant model constructed from cloud top temperature, middle level mel ting parameter and low level wet bulb temperature is the highest among all models, with a discriminant accuracy rate of 91.86%.
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基金项目:国家重点研发计划(2018YFF0300104)和国家气象中心预报员专项(Y201501)共同资助
引用文本:
陈双,谌芸,何立富,郭云谦,2019.我国中东部平原地区临界气温条件下降水相态判别分析[J].气象,45(8):1037-1051.
CHEN Shuang,CHEN Yun,HE Lifu,GUO Yunqian,2019.Discrimination Analysis of Snow and Rain Occurring Under Critical Temperature Conditions in Central and Eastern China[J].Meteor Mon,45(8):1037-1051.