Please wait a minute...
高级检索
高原气象  2018, Vol. 37 Issue (3): 863-871    DOI: 10.7522/j.issn.1000-0534.2018.00007
论文     
自动与人工观测霾日、雾日序列连续性分析
任芝花, 余予, 韩瑞, 冯明农
国家气象信息中心, 北京 100081
Analysis of Continuity of Fog, Light Fog and Haze Climate Series by Automatic Identification and Manual Observation
REN Zhihua, YU Yu, HAN Rui, FENG Mingnong
National Meteorological Information Centre, Beijing 100081, China
 全文: PDF 
摘要: 由原始观测数据统计显示,2014年全国雾霾(包括雾、轻雾和霾)日数偏高,尤其霾日数是2000-2013年均值的4.2倍。依据2014年雾霾现象保留人工观测或采用自动观测,将全国2 400余个国家站分为人工站和自动站,分别就两类站2014年雾霾现象日数与其历史序列进行了对比分析。结果表明,人工站2014年平均雾霾日数与其2000年以来平均状况及2013年平均雾霾日数接近;而自动站2014年平均雾霾日数明显偏高,成为2000年以来之最,且明显高于2013年统计结果。通过对比分析自动与人工观测方法表明,雾霾现象自动观测采用瞬间观测记录,是造成2014年全国雾霾日数异常偏高的主要原因。基于霾现象持续性特征,针对自动观测霾数据,研究确定了1天至少6个连续时次“现在天气现象”有霾记录,“连续天气现象”方记霾现象的订正方法。统计结果表明,订正前全国2014年平均霾日数为59天,而订正后下降为31天,基本与2013年持平。进一步分析表明,2000年以来我国霾发生频率呈增加趋势,尤其2013年和2014年,霾发生频率成为2000年以来之最。
关键词: 雾霾现象自动观测人工观测连续性    
Abstract: Based on the fog, light fog and haze daily data from more than 2 400 national level surface stations, comparisons were made between the statistics of 2014 and their historical series. Results showed that the national mean fog, light fog and haze days were 20, 154 and 59 respectively and were all highest values from the year of 2000. Especially, haze day of 2014 was 4.2 times of the means from 2000 to 2013, which may not match the actual conditions. Further analysis were presented by dividing the stations into two parts, as about 963 stations were carried out automatic identifications of the vision obstruction weather phenomenon from the beginning of 2014, while the other stations still maintained manual observations. The mean fog, light fog and haze days of manual stations in 2014 were close to their averages of recent decade and the statistics of 2013. As for the automatic stations, the mean values were rocketed to the highest starting from the year of 2000 and were extremely higher than the statistics of 2013. Through the analysis of the differences between automatic and manual observation methods and their data, the unusual higher values in 2014 were mainly ascribed to the weather phenomenon identification employed by automatic stations, as instantaneous occurrences of fog, light fog and haze were improperly written into the daily records. Based on the characteristics of haze persistence, correction method was studied on haze identification at automatic stations by using present weather phenomenon data. When at least six consecutive present weather phenomenon occurred in one day, haze was then written into the consecutive weather phenomenon record, i. e. the daily record and that day was consequently identified as a haze day. This method was verified by comparing the corrected data with the air quality conditions between 2013 and 2014 in 74 cities released by the Ministry of Environmental Protection, which shown a good agreement. The national mean haze day number of 2014 dropped down to about 31 days from about 59 days after correction, and the revised mean value was equal to that of 2013. The corrected data indicated that haze occurrence frequency had an increasing trend, and it peaked at 2013 and 2014 from the year of 2000.
Key words: Fog, light fog and haze    automatic identification    manual observation    continuity
收稿日期: 2017-10-01 出版日期: 2018-06-24
ZTFLH:  P413  
基金资助: 国家自然科学基金重大研究计划(91744209);中国气象局预报预测核心业务发展专项(CMAHX20160703);中国气象局气象关键技术集成与应用重点项目(CMAGJ2015Z16);公益性行业(气象)科研专项(GYHY201106038)
通讯作者: 余予(1981),男,江苏镇江人,高级工程师,主要从事气象资料分析与评估研究.E-mail:yuyu@cma.gov.cn     E-mail: yuyu@cma.gov.cn
作者简介: 任芝花(1969),女,山东招远人,正高级工程师,主要从事气象数据质量控制、分析与评估研究.E-mail:rzh@cma.gov.cn
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
任芝花
余予
韩瑞
冯明农

引用本文:

任芝花, 余予, 韩瑞, 冯明农. 自动与人工观测霾日、雾日序列连续性分析[J]. 高原气象, 2018, 37(3): 863-871.

REN Zhihua, YU Yu, HAN Rui, FENG Mingnong. Analysis of Continuity of Fog, Light Fog and Haze Climate Series by Automatic Identification and Manual Observation. Plateau Meteorology, 2018, 37(3): 863-871.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2018.00007        http://www.gyqx.ac.cn/CN/Y2018/V37/I3/863

邓学良, 石春娥, 姚晨, 等, 2015.安徽霾日重建和时空特征分析[J].高原气象, 34(4):1158-1166.Deng X L, Shi C E, Yao C, et al, 2015.Research of reconstruction and characteristics of hazes in Anhui[J].Plateau Meteor, 34(4):1158-1166.DOI:10.7522/j.issn.1000-0534.2014.00007.
丁一汇, 柳艳菊, 2014.近50 年我国雾和霾的长期变化特征及其与大气湿度的关系[J].中国科学:地球科学, 44:37-48.Ding Y H, Liu Y J, 2014.Analysis of long-term variations of fog and haze in China in recent 50 years and their relations with atmospheric humidity[J].Sci China:Earth Sci, 57:36-46.DOI:10.1007/s11430-013-4792-1.
环境保护部, 2015.2014中国环境状况公报[EB/OL].http://www.mep.gov.cn/hjzl/zghjzkgb/lnzghjzkgb/201605/P020160526564730573906.pdf.Ministry of Environmental Protection, 2015.2014 China Environmental Bulletin[EB/OL].http://www.mep.gov.cn/hjzl/zghjzkgb/lnzghjzkgb/201605/P020160526564730573906.pdf.[2017-10-01]
贾佳, 倪长健, 胡泽勇, 等, 2017.19802010年成都灰霾的变化特征及其与气候要素的关联性[J].高原气象, 36(2):517-527.Jia J, Ni C J, Hu Z Y, et al, 2017.Variation of haze and its relationship with climate change in Chengdu from 1980 to 2010[J].Plateau Meteor, 36(2):517-527.DOI:10.7522/j.issn.1000-0534.2016.00077.
廖国莲, 曾鹏, 郑凤琴, 等, 2011.19602009年广西霾日时空变化特征[J].应用气象学报, 22(6):732-736.Liao G L, Zeng P, Zheng F Q, et al, 2011.Spatial and temporal varations of hazes in Guangxi from 1960 to 2009[J].J Appl Meteor Sci, 22(6):732-736.
任芝花, 熊安元, 2007.地面自动站观测资料三级质量控制业务系统的研制[J].气象, 33(1):19-24.Ren Z H, Xiong A Y, 2007.Operational system development on three-step quality control of observation from AWS[J].Meteor Mon, 33(1):19-24.
司鹏, 高润翔, 2015.天津雾和霾自动观测和人工观测的对比评估[J].应用气象学报, 26(2):240-246.Si P, Gao R X, 2015.A comparative evaluation on automatic and manual observation of fog and haze in Tianjin[J].J Appl Meteor Sci, 26(2):240-246.
苏兆达, 白龙, 梁岱云, 2017.近15年南宁市霾日数变化特征及气象成因初步分析[J].高原气象, 36(3):826-834.Su Z D, Bai L, Liang D Y, 2017.Variations of haze days and its meteorological influences in Nanning since 2000[J].Plateau Meteor, 36(3):826-834.DOI:10.7522/j.issn.1000-0534.2016.00065.
王腾飞, 苏布达, 姜彤, 2014.气候变化背景下的雾霾变化趋势与对策[J].环境影响评价, 2014(1):15-17.Wang T F, Su B D, Jiang T, 2014.Variation trend of smog under climate change context and the strategies[J].Environ Impact Assess, 2014(1):15-17.
吴兑, 吴晓京, 李菲, 等, 2010.19512005年中国大陆霾的时空变化[J].气象学报, 68(5):680-688.Wu D, Wu X J, Li F, et al, 2010.Temporal and spatial variation of haze during 19512005 in Chinese mainland[J].Acta Meteor Sinica, 68(5):680-688.
吴兑, 吴晓京, 李菲, 等, 2011.中国大陆19512005年雾与轻雾的长期变化[J].热带气象学报, 27(2):146-151.Wu D, Wu X J, Li F, et al, 2011.Long-term variation of fog and mist in 19512005 in mainland China[J].J Trop Meteor, 27(2):146-151.
颜娇珑, 张武, 单云鹏, 等, 2016.西北东部霾的时空特征与天气特征研究[J].高原气象, 35(4):1073-1086.Yan J L, Zhang W, Shan Y P, et al, 2016.Spatio-temporal distribution of aerosol and weather characteristics during haze over the Eastern Northwest China[J].Plateau Meteor, 35(4):1073-1086.DOI:10.7522/j.issn.1000-0534.2015.00028.
张人禾, 李强, 张若楠, 2014.2013 年1 月中国东部持续性强雾霾天气产生的气象条件分析[J].中国科学:地球科学, 44:27-36.Zhang R H, Li Q, Zhang R N, 2014.Meteorological conditions for the persistent severe fog and haze event over eastern China in January 2013[J].Sci China:Earth Sci, 57:26-35.DOI:10.1007/s11430-013-4774-3.
中国气象局, 2003.地面气象观测规范[S].北京:气象出版社.China Meteorological Administration, 2003.Guidance of surface meteorological observation[S].Beijing:China Meteorological Press.
中国气象局, 2005.地面气象观测数据文件和记录薄表格式[S].北京:气象出版社, 18-65.China Meteorological Administration, 2005.File format of surface meteorological observation data file and observation record sheet[S].Beijing:China Meteorological Press, 18-65.
中国气象局, 2013.中国气象局综合观测司关于做好全国地面气象观测业务调整工作的通知:气测函[2013]321号[Z].北京:中国气象局.China Meteorological Administration, 2013.Integrated Observations Department of CMA released letter No.321:Notice on the adjustments of the national operational surface meteorological observation form the Integrated Observations Department of CMA[Z].Beijing:China Meteorological Administration.
中国气象局, 2014.中国气象局预报司、观测司关于调整霾天气现象观测规定和对2013年雾、霾观测数据订正的通知:气预函[2014]4号[Z].北京:中国气象局.China Meteorological Administration, 2014.Forecasting and Networking Department of CMA released letter No.4:Notice on the adjustments of the haze weather phenomenon observation and on the revision of the fog and haze observation data form the Forecasting and Network Department and the Integrated Observations Department of CMA[Z].Beijing:China Meteorological Administration.
中国气象局, 2015.观测司关于地面气象观测业务运行有关工作的通知:气测函[2015]45号[Z].北京:中国气象局.China Meteorological Administration, 2015.Integrated Observations Department of CMA released letter No.45:Notice on the operational works of the surface meteorological observation form the Integrated Observations Department of CMA[Z].Beijing:China Meteorological Administration.
[1] 贾洋, 崔鹏. 高山区多时间尺度Anusplin气温插值精度对比分析[J]. 高原气象, 2018, 37(3): 757-766.
[2] 吴蔚, 梁卓然, 刘校辰. CDF-T方法在站点尺度日降水预估中的应用[J]. 高原气象, 2018, 37(3): 796-805.
[3] 余予, 任芝花, 孟晓艳. 中国结冰现象序列的建立及气候变化分析[J]. 高原气象, 2018, 37(2): 553-559.
[4] 赵煜飞, 张强, 余予, 杨贵. 中国小时风速数据集研制及在青藏高原地区的应用[J]. 高原气象, 2017, 36(4): 930-938.
[5] 李京校, 郭凤霞, 扈海波, 李如箭, 钱慕晖, 肖稳安. 北京及其周边地区SAFIR和ADTD闪电定位资料对比分析[J]. 高原气象, 2017, 36(4): 1115-1126.
[6] 万晓敏 田伟红 何晓欢. 加密FY-2G云导风质量评估及其在GRAPES_RAFS系统中的应用分析[J]. 高原气象, 2017, 36(1): 0-0.
[7] 焦鹏程, 王振会, 楚志刚, 韩静, 张帅, 朱艺青. 基于傅里叶谱分析的天气雷达图像插值方法[J]. 高原气象, 2016, 35(6): 1683-1693.
[8] 谭剑波, 李爱农, 雷光斌. 青藏高原东南缘气象要素Anusplin和Cokriging空间插值对比分析[J]. 高原气象, 2016, 35(4): 875-886.
[9] 吴翀, 刘黎平, 吴海涛. 多部X波段天气雷达测量偏差分布及组网拼图结果分析[J]. 高原气象, 2016, 35(3): 823-833.
[10] 闵文彬, 李跃清, 周纪. 青藏高原东侧MODIS地表温度产品验证[J]. 高原气象, 2015, 34(6): 1511-1516.
[11] 赵煜飞, 朱江. 近50年中国降水格点日值数据集精度及评估[J]. 高原气象, 2015, 34(1): 50-58.
[12] 叶冬, 申彦波, 杜江, 艾生, 程兴宏. 吐鲁番气象站周边典型建筑对日照时数的影响分析[J]. , 2014, 33(6): 1712-1721.
[13] 张涛, 苗春生, 王新. LAPS与STMAS地面气温融合效果对比试验[J]. 高原气象, 2014, 33(3): 743-752.
[14] 戴晓燕, 过仲阳, 吴健平, 黎薇, 林珲. 1998年夏季青藏高原上东移MCS环境场特征的聚类分析[J]. 高原气象, 2007, 26(4): 701-707.
[15] 曹晓钟, 王强. 神经网络在气象观测资料优化中的应用研究[J]. 高原气象, 2001, 21(1): 96-101.