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基于天气背景天津地区重污染天气特征分析
引用本文:蔡子颖,韩素芹,汪靖,姚青,张敏,刘敬乐.基于天气背景天津地区重污染天气特征分析[J].环境科学学报,2017,37(10):3906-3917.
作者姓名:蔡子颖  韩素芹  汪靖  姚青  张敏  刘敬乐
作者单位:1. 天津市环境气象中心, 天津 300074;2. 天津市气象科学研究所, 天津 300074,天津市气象科学研究所, 天津 300074,天津市气象台, 天津 300074,天津市环境气象中心, 天津 300074,1. 天津市环境气象中心, 天津 300074;2. 天津市气象科学研究所, 天津 300074,天津市气象科学研究所, 天津 300074
基金项目:环保公益行业专项(No.201409001);国家科技支撑计划(No.2014BAC23B01);国家国际科技合作专项项目(No.2015DFA20870-02);天津市气象局课题(No.201716ybxm10,201625ybxm18);中国气象局预报员专项(No.CMAYBY2016-005)
摘    要:以天津地区长序列观测PM_(2.5)质量浓度资料为依托,基于天气背景对2014—2016年天津地区重污染天气特征进行分析,并以此为基础评估天津环境气象数值模式(WRF/Chem)在不同天气条件下的模拟效果.结果显示:2009—2016年天津地区重污染天气为341 d,约占全部天数的11.7%,重污染天气主要出现在每年的10月—次年3月,约占全年的82%,重污染天气出现的地面形势主要为锋前低压区、低压槽前、均压场和高压后,4类天气类型占所有重污染天气的73%.同一天气背景下,PM_(2.5)质量浓度模拟值与实况值之间的误差有相似之处,低压槽天气时细颗粒污染浓度模拟明显偏低;冷锋前低压区、华北地形槽和低压过程模拟值略有偏低;高压前和高压底天气模拟值略微偏高;数值模式天津地区重污染TS(Threat score)评分为0.68,漏报与低压槽辐合线模拟位置偏差、冷空气受污染反馈作用影响、小尺度闭合低压区未准确模拟3个因素密切相关;空报主要与冷空气过程影响时间模拟偏差、高压中心位置偏差及其输送通道建立时间影响密切相关.

关 键 词:天气类型  重污染天气  数值模拟  天津
收稿时间:2017/3/9 0:00:00
修稿时间:2017/4/10 0:00:00

Analysis of synoptic characteristics of heavy pollution in Tianjin based on weather background
CAI Ziying,HAN Suqin,WANG Jing,YAO Qing,ZHANG Min and LIU Jinle.Analysis of synoptic characteristics of heavy pollution in Tianjin based on weather background[J].Acta Scientiae Circumstantiae,2017,37(10):3906-3917.
Authors:CAI Ziying  HAN Suqin  WANG Jing  YAO Qing  ZHANG Min and LIU Jinle
Institution:1. Tianjin Environmental Meteorological Center, Tianjin 300074;2. Tianjin Institute of Meteorology, Tianjin 300074,Tianjin Institute of Meteorology, Tianjin 300074,Tianjin Meteorological Observatory, Tianjin 300074,Tianjin Environmental Meteorological Center, Tianjin 300074,1. Tianjin Environmental Meteorological Center, Tianjin 300074;2. Tianjin Institute of Meteorology, Tianjin 300074 and Tianjin Institute of Meteorology, Tianjin 300074
Abstract:Based on the long-term PM2.5 mass concentration data in Tianjin, this study analyses characteristics of heavy pollution weather in Tianjin under different backgrounds from 2014 to 2016 and evaluates the simulation results derived from WRF/Chem modelunder different weather conditions. Results showed that the total number of heavy pollution days were 341 in Tianjin during 2009-2016, which accounted for~11.7% of all days.Heavy pollution weather mainly occurs during October-March, which accounted for~82% of all heavy pollution days. The surface patterns favoring the formation of heavy pollution weather mainly include the low pressure in front of cold front,front of the upper trough, the saddle and the high-pressure rear. These four patterns account for 73% of all heavy pollution weather events.The deviation between simulated and observed PM2.5 mass concentrations showed similarities for the same weather background. Simulation of fine particle pollution is remarkably lower in the background of upper trough, slightly lower in the backgroundof flow pressure in front of cold front, topographic trough and low pressure system, and slightly higher in front of and at the bottom of the high pressure. The TS of numerical model on heavy pollution was 0.68. There were multiple causes for vacancy-forecast, including the simulationof position deviation of convergence line, effects of pollution feedback about cold air, and simulation of small scale closed low pressure area. There were also multiple causes for failed-forecast, including the affecting time of the cold air process, bias of the position of high pressure center and the time for the establishment of pollutants transport channel.
Keywords:synoptic types  heavy pollution weather  numerical simulation  Tianjin
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