Article(id=1241408718424821822, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728316800000, receivedDateStr=2024-10-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773904502730, onlineDateStr=2026-03-19, pubDate=1745078400000, pubDateStr=2025-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773904502730, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773904502730, creator=13701087609, updateTime=1773904502730, updator=13701087609, issue=Issue{id=1241408710791189399, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='4', pageStart='1777', pageEnd='2368', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773904500911, creator=13701087609, updateTime=1773904624658, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241409229878259747, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241409229878259748, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1858, endPage=1868, ext={EN=ArticleExt(id=1241408718772949077, articleId=1241408718424821822, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Assess the applicability of satellite and reanalysis data in Guangdong-Hongkong-Macao regions based on ozonesonde measurements, columnId=1234106386020365051, journalTitle=China Environmental Science, columnName=Air Pollution Control, runingTitle=null, highlight=null, articleAbstract=

Based on the ozonesonde data in Guangdong, Hong Kong, and Macao regions from 2022 to 2023, the vertical distribution characteristics of O3 concentration were analyzed, and the applicability of Aqua satellite AIRS O3 vertical profile product and ERA5 reanalysis O3 vertical profile product were evaluated by using self-organizing map neural network (SOM) method. The vertical distribution of O3 in the Greater Bay Area exhibited significant seasonal variations. In spring, summer, and winter, the ozone vertical distribution displayed a unimodal structure, with peak concentrations located near 700, 950, and 300 hPa, respectively. In contrast, the vertical distribution in autumn showed a bimodal structure, with peaks near 925 and 400hPa. The vertical differences in O3 between stations were relatively small, with deviations between Guangdong and Hong Kong stations ranging from -3.2% to 11.0%. The quality of AIRS and ERA5 data in autumn and winter within the troposphere was better than that in spring and summer. At 850~200hPa, both AIRS and ERA5 data showed relatively good quality, with seasonal relative average deviations (Rad) ranging from 16.5% to 25.8% for AIRS and 15.1% to 25.7% for ERA5. The average correlation coefficients (r) for the seasons ranged from 0.47 to 0.75 for AIRS and 0.23 to 0.74 for ERA5. Below 850 hPa, the quality of AIRS and ERA5 data was relatively bad, with average value of r were 0.34 and -0.15. The vertical distribution of O3 was categorized into 5 types. Among these, the data quality of AIRS and ERA5 was best under the type 1distribution structure, while it was worst under the type 2 and type 3 structures. Type 1 occurred more frequently in autumn (43%) and winter (61%), whereas type 2 and type 3 were more common in summer (66%). Type 4 and type 5 occurred more frequently in spring (85%).

, correspAuthors=Ting-yuan LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yu GONG, Ting-yuan LI, Jin SHEN, Jing-yang CHEN), CN=ArticleExt(id=1241408722736566712, articleId=1241408718424821822, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=利用臭氧探空数据评估卫星及再分析资料在粤港澳地区的适用性, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

基于2022~2023年粤港澳地区臭氧(O3)探空观测资料,分析O3浓度垂直分布特征变化趋势,并结合自组织映射神经网络(SOM)分型方法,评估了Aqua卫星大气红外探测器(AIRS)O3垂直廓线产品以及ERA5再分析资料的O3垂直廓线产品在粤港澳地区的适用性.结果表明:①粤港澳地区O3垂直分布季节性差异较为显著,春夏冬季呈单峰分布结构,峰区分别位于700,950和300hPa附近,秋季呈双峰分布结构,峰区位于925和400hPa附近.站点间差异较小,广东省各站点与香港站点的O3廓线年平均偏差介于-3.2%~11.0%之间.②对流层内秋冬季AIRS和ERA5数据质量好于春夏季.850~200hPa,AIRS和ERA5数据质量相对较好,各季节相对平均偏差(Rad)平均值分别介于16.5%~25.8%和15.1%~25.7%之间,相关系数(r)平均值分别介于0.47~0.75和0.23~0.74之间;而在850hPa以下,AIRS和ERA5数据质量相对较差,AIRS数据略好于ERA5数据,Rad平均值分别为31.6%和40.9%,r平均值分别为0.34和-0.15.③将O3垂直分布分为5型,其中,AIRS与ERA5资料在1型分布结构下数据质量最好,而在2型和3型分布结构下数据质量最差.1型在秋冬季出现频率较高(分别为43%和61%),2型和3型在夏季出现频率较高(共66%),4型和5型在春季出现频率较高(共85%).

, correspAuthors=李婷苑, authorNote=null, correspAuthorsNote=
* 责任作者,高级工程师,
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龚宇(1996-),男,江苏南通人,工程师,硕士,主要从事环境气象研究.发表论文7篇..

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龚宇(1996-),男,江苏南通人,工程师,硕士,主要从事环境气象研究.发表论文7篇..

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龚宇(1996-),男,江苏南通人,工程师,硕士,主要从事环境气象研究.发表论文7篇..

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审图号:GS(2020)4814

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(a)春季;(b)夏季;(c)秋季;(d)冬季;(e)全年

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(a)AIRS与探空数据的Rad分布;(b)ERA5与探空数据的Rad分布;(c)ERA5与探空数据的Rad值减去AIRS与探空数据的Rad值;(d)AIRS与探空数据的r值分布;(e)ERA5与探空数据的r值分布;(f)ERA5与探空数据的r值减去AIRS与探空数据的r

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(a)AIRS与探空数据的Rad值分布;(b)ERA5与探空数据的Rad值分布;(c)ERA5与探空数据的Rad值减去AIRS与探空数据的Rad值;(d)AIRS与探空数据的r值分布;(e)ERA5与探空数据的r值分布;(f)ERA5与探空数据的r值减去AIRS与探空数据的r

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(a)1型;(b)2型;(c)3型;(d)4型;(e)5型

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(a)AIRS与探空数据的Rad值分布;(b)ERA5与探空数据的Rad值分布;(c)AIRS与探空数据的r值分布;(d)ERA5与探空数据的r值分布

, figureFileSmall=24igo+qyrYO4YGWypqiZRQ==, figureFileBig=bjliwK12eI1nYK2hDSpb/g==, tableContent=null), ArticleFig(id=1241408730517000438, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408718424821822, language=EN, label=Table 1, caption=

O3 sounding frequency in Guangdong, Hong Kong, and Macao

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季节香港清远河源汕头阳江总量
141721181989
132018182392
122316111880
12474532
合计5164625165293
), ArticleFig(id=1241408730751881475, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408718424821822, language=CN, label=表1, caption=

粤港澳O3探空频次信息

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季节香港清远河源汕头阳江总量
141721181989
132018182392
122316111880
12474532
合计5164625165293
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利用臭氧探空数据评估卫星及再分析资料在粤港澳地区的适用性
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龚宇 1, 2 , 李婷苑 1, 2, * , 沈劲 3 , 陈靖扬 1, 2
中国环境科学 | 大气污染与控制 2025,45(4): 1858-1868
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中国环境科学 | 大气污染与控制 2025, 45(4): 1858-1868
利用臭氧探空数据评估卫星及再分析资料在粤港澳地区的适用性
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龚宇1, 2 , 李婷苑1, 2, * , 沈劲3, 陈靖扬1, 2
作者信息
  • 1.广东省生态气象中心(珠三角环境气象预报预警中心),广东 广州 510640
  • 2.广东省南岭森林大气环境与碳中和野外科学观测研究站,广东 广州 511443
  • 3.广东省生态环境监测中心,国家环境保护区域空气质量监测重点实验室,广东省环境保护大气二次污染研究重点实验室,广东 广州 510308
  • 龚宇(1996-),男,江苏南通人,工程师,硕士,主要从事环境气象研究.发表论文7篇..

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* 责任作者,高级工程师,
Assess the applicability of satellite and reanalysis data in Guangdong-Hongkong-Macao regions based on ozonesonde measurements
Yu GONG1, 2 , Ting-yuan LI1, 2, * , Jin SHEN3, Jing-yang CHEN1, 2
Affiliations
  • 1.Guangdong Ecological Meteorological Centre, Pearl River Delta Center for Environmental Meteorology Prediction and Warning, Guangzhou 510640, China
  • 2.Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou 511443, China
  • 3.Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Secondary Air Pollution Research, Guangdong Ecological Environmental Monitoring Center, Guangzhou 510308, China
出版时间: 2025-04-20
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基于2022~2023年粤港澳地区臭氧(O3)探空观测资料,分析O3浓度垂直分布特征变化趋势,并结合自组织映射神经网络(SOM)分型方法,评估了Aqua卫星大气红外探测器(AIRS)O3垂直廓线产品以及ERA5再分析资料的O3垂直廓线产品在粤港澳地区的适用性.结果表明:①粤港澳地区O3垂直分布季节性差异较为显著,春夏冬季呈单峰分布结构,峰区分别位于700,950和300hPa附近,秋季呈双峰分布结构,峰区位于925和400hPa附近.站点间差异较小,广东省各站点与香港站点的O3廓线年平均偏差介于-3.2%~11.0%之间.②对流层内秋冬季AIRS和ERA5数据质量好于春夏季.850~200hPa,AIRS和ERA5数据质量相对较好,各季节相对平均偏差(Rad)平均值分别介于16.5%~25.8%和15.1%~25.7%之间,相关系数(r)平均值分别介于0.47~0.75和0.23~0.74之间;而在850hPa以下,AIRS和ERA5数据质量相对较差,AIRS数据略好于ERA5数据,Rad平均值分别为31.6%和40.9%,r平均值分别为0.34和-0.15.③将O3垂直分布分为5型,其中,AIRS与ERA5资料在1型分布结构下数据质量最好,而在2型和3型分布结构下数据质量最差.1型在秋冬季出现频率较高(分别为43%和61%),2型和3型在夏季出现频率较高(共66%),4型和5型在春季出现频率较高(共85%).

粤港澳  /  臭氧(O3)  /  大气红外探测器(AIRS)  /  ERA5  /  评估  /  自组织映射神经网络(SOM)

Based on the ozonesonde data in Guangdong, Hong Kong, and Macao regions from 2022 to 2023, the vertical distribution characteristics of O3 concentration were analyzed, and the applicability of Aqua satellite AIRS O3 vertical profile product and ERA5 reanalysis O3 vertical profile product were evaluated by using self-organizing map neural network (SOM) method. The vertical distribution of O3 in the Greater Bay Area exhibited significant seasonal variations. In spring, summer, and winter, the ozone vertical distribution displayed a unimodal structure, with peak concentrations located near 700, 950, and 300 hPa, respectively. In contrast, the vertical distribution in autumn showed a bimodal structure, with peaks near 925 and 400hPa. The vertical differences in O3 between stations were relatively small, with deviations between Guangdong and Hong Kong stations ranging from -3.2% to 11.0%. The quality of AIRS and ERA5 data in autumn and winter within the troposphere was better than that in spring and summer. At 850~200hPa, both AIRS and ERA5 data showed relatively good quality, with seasonal relative average deviations (Rad) ranging from 16.5% to 25.8% for AIRS and 15.1% to 25.7% for ERA5. The average correlation coefficients (r) for the seasons ranged from 0.47 to 0.75 for AIRS and 0.23 to 0.74 for ERA5. Below 850 hPa, the quality of AIRS and ERA5 data was relatively bad, with average value of r were 0.34 and -0.15. The vertical distribution of O3 was categorized into 5 types. Among these, the data quality of AIRS and ERA5 was best under the type 1distribution structure, while it was worst under the type 2 and type 3 structures. Type 1 occurred more frequently in autumn (43%) and winter (61%), whereas type 2 and type 3 were more common in summer (66%). Type 4 and type 5 occurred more frequently in spring (85%).

Guangdong-Hongkong-Macao regions  /  ozone (O3)  /  Atmospheric Infrared Sounder (AIRS)  /  ERA5  /  assess  /  self-organizing map neural networks (SOM)
龚宇, 李婷苑, 沈劲, 陈靖扬. 利用臭氧探空数据评估卫星及再分析资料在粤港澳地区的适用性. 中国环境科学, 2025 , 45 (4) : 1858 -1868 .
Yu GONG, Ting-yuan LI, Jin SHEN, Jing-yang CHEN. Assess the applicability of satellite and reanalysis data in Guangdong-Hongkong-Macao regions based on ozonesonde measurements[J]. China Environmental Science, 2025 , 45 (4) : 1858 -1868 .
臭氧(O3)和细颗粒物是对流层大气中的重要污染物,近年来随着大气污染综合治理力度的加大,国内PM2.5浓度总体呈下降趋势,各地空气质量大幅改善[1-4].广东省PM2.5已多年达到世卫组织第二阶段标准,但是O3浓度一直居高不下,自2015年起O3取代颗粒物成为影响全省空气质量指数(AQI)达标率的最关键因素[5-6],当前臭氧污染过程在珠江三角洲特大城市群频繁发生[7-10].
O3作为一种高反应性温室气体,可通过辐射强迫影响气候,近地面高浓度O3对植被作物的生长和人类健康都会构成威胁[11-16].研究发现地表臭氧污染与对流层臭氧变化密切相关,粤港澳属热带和亚热带季风气候,同处于高空东、西风系交替影响过渡区,温带、热带各类天气活动频繁,影响着对流层内臭氧的形成、积累、沉积和输送,全面了解对流层O3浓度垂直分布对于解析南方地区高臭氧污染过程成因具有重要意义[17-20].当前,O3垂直浓度观测仪器被广泛应用于获取地面至平流层区域内的O3浓度廓线,主要有探空气球、激光雷达平台(地基、机载、星载)、微波辐射计等[21-26].其中,探空气球观测因其探测高度高、可靠性强、灵敏度和垂直分辨率高等优势,被广泛应用于O3浓度垂直特征分析、传输机制研究以及对其他垂直探测资料验证[27-32],但是由于O3探空其成本较高且对气球放空地点选址苛刻等诸多因素,很难进行大面积布点观测.而卫星观测和再分析产品虽然垂直分辨率和灵敏度不及探空观测,但其具备数据获取便捷、覆盖全球等优势,弥补了O3探空在时间和空间上不连续的缺陷,通常在没有探空站点的地区或探空观测数据缺失的时段,卫星和再分析产品往往是较为常用的O3浓度垂直分布来源[33-35].
尽管如此,借助卫星、再分析数据研究对流层臭氧仍存在固有的局限性,卫星数据因其测量技术和反演算法实现细节(例如光谱数据和算法模型参数的选择)会对反演结果产生较大影响[36-38].Zhang等[39]利用北京地区探空数据评估多种卫星臭氧垂直廓线产品,结果表明卫星反演结果与臭氧探空廓线整体较为接近,但均存在局部高度处差异较大的问题.再分析资料对于大气成分再分析数据集约束对流层臭氧变化的能力以及对不同数据来源对流层臭氧含量的差异性缺乏研究,影响数据质量[40-41].Katragkou等[42]利用再分析资料对欧洲地面臭氧进行研究,发现近地面臭氧在冬季呈现负偏差,在暖季呈现正偏差.
目前为止,卫星及再分析臭氧产品的评估研究多是针对欧洲地区[43-44],中国区域由于缺乏较长序列垂直观测数据,相关评估工作仍较为稀缺,国内研究也多集中在中北部地区,在华南地区适用性评估尚未得到深入的探索.针对上述问题,本文借助粤港澳地区探空站点O3浓度垂直资料对Aqua卫星大气红外探测器(AIRS)O3浓度垂直廓线产品、ERA5再分析O3浓度垂直廓线产品进行了比较,评估小时产品在对流层(100hPa以下)各高度范围的探测效果,有助于更好了解AIRS和ERA5O3浓度垂直廓线产品在粤港澳地区的适用性,为完善粤港澳地区O3三维监测、提高空气污染预报能力和制定空气质量政策提供支撑.
探空观测是当前常用的高灵敏度、高分辨率O3浓度垂直探测手段[45],研究所使用的探空站点分别位于广东阳江、广东清远、广东河源、广东汕头和香港京士柏(图1),所处位置基本等距分布于粤港澳四方位及中心区域.
各站点气球探测时间均在北京时间12:00时前后,探测高度可达35km.广东省四站点O3探空观测垂直分辨率约为5m,各站点约4d开展一次探空观测;香港O3探空垂直分辨率为10m,约一周进行一次探空观测.选取2022年10月至2023年10月5个探空站点共293组探空数据,各站点详细数据情况见表1.采用探空观测数据评估对流层内卫星和再分析数据在粤港澳地区的适用性,中国大陆对流层顶气压大概在100hPa附近[46],因此设定对比高度范围为1000~100hPa.
AIRS(https://disc.gsfc.nasa.gov/)是太阳同步轨道卫星Aqua上的传感器之一,与高级微波探测装置(AMSU)和巴西湿度探测仪(HSB)相结合,共同构成了一个由可见光、红外和微波传感器组成的创新型大气探测组块,可提供大气温度、痕量气体以及地表和云特性的三维信息.研究使用第7版本的3级AIRS O3浓度垂直廓线产品,AIRS使用地方时13:30的数据,水平分辨率为1°×1°,垂直方向上从1000~1hPa共24层,其中100hPa高度以下共计12层(即1000,925,850,700,600,500,400,300,250,200,150和100hPa),AIRS卫星O3监测数据被广泛应用于各类痕量气体的月季尺度垂直分布特征变化分析,是目前科研业务常用的O3卫星产品之一[47-48].
ERA5(https://cds.climate.copernicus.eu/cdsapp#!/)再分析数据是欧洲中期天气预报中心(ECMWF)制作的第五代全球气候再分析数据集,可提供大气、海浪和陆地表面等参数的小时数据产品.ERA5产品融合了许多O3卫星观测结果,其O3的分布格局和趋势较为可靠.本研究使用ERA5再分析数据集的O3质量浓度小时数据产品,水平分辨率为0.25°×0.25°,垂直方向上气压范围为1000~1hPa,共计37层,其中100hPa高度以下共27层,为保持检验高度和观测时间的一致性,本研究使用北京时间12:00时的再分析数据结果,垂直浓度层选择与AIRS产品相对应的12层气压高度.
(1)评估方法:以探空数据作为标准值,采用距离最近原则挑选与探空站点经纬度最近的卫星和再分析格点作为匹配点位,使用相对平均偏差(Rad)、相关系数(r)检验AIRS和ERA5产品的性能,计算方法如下:
式中:Yi为被检验数据,即AIRS和ERA5O3浓度数据,Xi为探空数据,n为数据总组数.Rad值越小,表明被检验数据与探空数据间的O3浓度差越小.
(2)分型方法:在对O3浓度垂直结构分类时,采用自组织映射神经网络(SOM)聚类算法.与其他聚类算法相比,SOM算法的优点是拓扑固定,聚类节点之间排列较为规则,即相似的节点距离较近,差异较大的节点距离较远[49-50],SOM代码源自MATLAB SOM工具箱,该工具箱可从芬兰赫尔辛基理工大学免费获得(http://www.cis.hut.fi/projects/somtoolbox/).与其他分型方法一样,SOM分型也需要事先指定聚类数目,本研究使用链接网络概念来确定O3浓度垂直分布类型的数目范围[51].
图2给出了各探空站点O3浓度四季及全年的垂直分布特征,可以看到,各站点O3浓度垂直分布特征的差异相对较小,站点间O3浓度分布一致性高,广东省四站点与香港站点O3浓度廓线年平均偏差分别为11.0%(清远)、1.6%(河源)、0.6%(汕头)、-3.2%(阳江).在季节变化上O3浓度垂直分布差异性较为显著,冬春季O3浓度随高度升高而波动上升,O3浓度垂直分布呈单峰型.除清远外,春季各站点在700hPa附近存在峰区,峰区峰值介于145~165μg/m3之间;冬季各站点峰区大约出现在400~250hPa之间,峰区峰值介于120~145μg/m3之间.夏季O3浓度垂直分布亦呈单峰型,850hPa高度以下,O3浓度相对较高,清远站点峰区最为明显,峰区峰值出现在950hPa高度附近,各站点峰值浓度差异较大,介于75~140μg/ m3之间;秋季O3浓度垂直分布呈双峰型,与夏季相比,秋季850hPa以下O3峰区更为明显,各站点峰区峰值均位于925hPa高度附近(峰值介于95~125µg/m3之间),此外对流层上层500~200hPa也出现O3峰区,峰区峰值均位于400hPa附近(峰值介于125~150μg/m3之间).
对比AIRS、ERA5与探空数据的差异,如图3所示为探空、卫星AIRS和再分析ERA5的平均O3浓度廓线比较,AIRS和ERA5数据在850hPa以下O3浓度普遍偏低,700~300hPa,AIRS始终呈现较大的O3浓度值,而ERA5则与探空结果较为接近,从300hPa到对流层顶,AIRS和ERA5的O3浓度再次出现低估的情况,AIRS资料的对比结果和Zhang等[39]在北京探空站点得出的AIRS卫星资料与探空资料O3浓度廓线对比结果一致.另外,从图4探空与对应时段AIRS、ERA5数据的比对散点图也可以看到,O3浓度小于200μg/m3时,各组散点近似集中在浓度1:1轴附近,不存在明显偏斜倾向,但当O3浓度大于200μg/m3时,AIRS数据出现明显低估情况,100hPa以下所有时段所有高度累积有效数据共2956组,卫星遥感资料与探空资料的Rad值和r值分别为24%和0.77,总体略优于ERA5的再分析资料(Rad=26%、r=0.75).
为进一步了解AIRS、ERA5各高度层O3浓度资料在不同季节下的数据质量,图5给出了不同季节下AIRS、ERA5与探空数据的比对结果.
可见,AIRS和ERA5资料均在秋季r值较高、冬春季Rad值较小,850hPa以上r平均值较高.与其余高度相比,850hPa以下四个季节AIRS、ERA5O3资料与探空O3资料的偏差较大,相关性较小,Rad平均值分别为31.6%和40.9%,r平均值分别为0.34和-0.15.850hPa以下大气运动受地表动力热力影响较大,是湍流混合、对流活动的主要发生区域,O3浓度受气象条件、前体物排放等诸多复杂因素影响,垂直分布形势多变,加之卫星遥感在近地面信号强度受限,导致产品适用性较差.对于850~200hPa高度,产品评估结果明显优于850hPa以下的评估结果,AIRS和ERA5资料在秋冬季各高度层的表现相对优于春夏季,各季节Rad平均值分别介于16.5%~25.8%和15.1%~25.7%之间,r平均值分别介于0.47~0.75和0.23~0.74之间.在对流层顶(200~100hPa),整体上看Rad值有所增大相关性降低,观测资料在对流层顶适用性转差.此外,AIRS资料与探空资料的Rad值在夏秋季700~500hPa高度和秋冬季200~100hPa高度均出现明显偏高情况,但r值也对应较大,说明AIRS资料虽然与探空结果浓度值存在较大偏差,但仍可较好地表征O3浓度变化趋势.
再从AIRS与ERA5O3浓度廓线资料评估结果的差值比对来看(图5c、5f,红色代表AIRS资料优于ERA5资料的区域,蓝色则ERA5资料较优),AIRS资料略优于ERA5资料.850hPa以下,AIRS资料全面优于ERA5资料,AIRS资料Rad值较小、r值较高.850hPa以上,各季节产品优势评估相对复杂:春季AIRS资料整体较优,仅部分高度Rad值略高于ERA5资料;夏季400~100hPa高度,AIRS资料偏差小相关性高,适用性优于ERA5资料,其余高度AIRS产品相关性高但偏差较大;秋冬季600~200hPa高度,ERA5产品较优,其余高度ERA5产品虽偏差较小但相关性较低.
为了解产品在不同地区各高度层的适用性,图6给出了不同站点下AIRS、ERA5资料与探空资料的Rad值和r值垂直分布图.可以看到,AIRS产品各站点Rad值在11.0%~46.1%之间、r值在0.09~0.88之间,不同站点间偏差与相关性特征较为相似.各站点在1000~900,700~500,200hPa高度均出现Rad大值区,该范围内各站点Rad值在20.7%~46.1%之间; 800~350hPa高度均为高相关性区域,该范围内各站点相关系数均在0.5以上.对于ERA5产品,研究时段内香港站点的评估结果较差,除500~200hPa数据质量相对一般外(Rad值13.0%~26.0%、r值0.14~0.54),其余高度上Rad值在30%以上,r值接近0.不同于香港站点,清远、河源、汕头、阳江4站点ERA5与探空的Rad值和r值分布特征则较为一致,850hPa以下各站点Rad值较大,r值较小,850hPa以上除河源站点在300hPa相关性较小外,其余站点偏差小(Rad值10.5%~28.6%),相关性高(r值0.41~0.91).
进一步比对AIRS与ERA5评估结果差异(图6c、6f),与季节对比结果相似,850hPa以下,AIRS产品全面优于ERA5产品,850hPa以上各站点产品优势评估较为复杂.对于香港站点,850hPa以上AIRS产品较优,而清远、河源、汕头、阳江站点850hPa以上总体呈现Rad值ERA5产品较小而相关性AIRS产品较高的情况.
考虑到传统的按照季节、区域来分析O3浓度廓线产品的适用性,可能会掩盖一些特定O3浓度垂直分布结构下的产品适用性特征,而聚类技术则是对具有相似结构的O3浓度廓线进行分组,从而实现不同O3浓度垂直分布类型下的数据特征分析及相关产品对比评估.研究不同O3浓度垂直分布结构下ERA5、AIRS产品的适用效果,能够更加全面了解产品适用性特征及适用性差异的来源.
利用SOM分型算法对探空站点O3浓度垂直廓线数据进行分类,图7给出了各站点五种分布型下O3浓度廓线.结果表明,5种O3浓度垂直分布型出现频率分别在13.8%~26.2%之间.按照O3浓度垂直分布特征,可将1型2型归为双峰型结构,4型5型归为无峰结构,3型为双峰型向无峰型的过度结构,其中双峰1型占比为24.7%,峰区峰值位于900hPa和400hPa高度附近;双峰2型占比18.7%,与双峰1型相比,低空O3峰区更加明显但峰值高度无明显变化,而高空峰区峰值高度则上移至300hPa附近;3型为过度结构,双峰逐渐趋于平缓,占比为16.6%;4型5型占比分别为13.8%和26.2%,近地面至对流层顶,O3浓度分布整体呈波动上升的特征,5型相较于4型,整体浓度更高,近地面与对流层顶O3浓度差值更小.
结合各季节O3浓度垂直分布型出现频率(图8)和不同垂直分布型下AIRS、ERA5与探空数据的比对结果(图9)可见,在200~100hPa高度,5种分布型下评估结果差异相对较小,而在200hPa高度以下,5种分布型下的评估结果差异相对较大.200hPa以下,1型的评估结果优于其他分布型,Rad平均值最小(分别为19.6%和18.9%),r平均值最高(分别为0.58和0.38),主要出现在秋季和冬季,出现频率分别高达43%和61%;2型和3型期间ERA5和AIRS产品评估结果则较其他垂直分布型态明显偏差,Rad平均值均高于30%,r平均值均低于0.22,这两种O3浓度垂直结构主要出现在夏季,总占比高达66%.此外,2型3型臭氧垂直分布结构在500~700hPa高度,AIRS数据Rad值显著偏高,而其他分布型并未出现该特征,2型3型主要出现在夏秋冬三季,且夏季1型廓线占比低,因此夏季700~500hPa出现Rad值异常偏高情况,秋季次之.4型和5型期间ERA5和AIRS产品评估结果介于1型和2型之间,ERA5和AIRS产品在850hPa以下r值小、Rad值较大,4型在500~400hPa、5型在500~300hPa产品评估结果相对较好,这两种O3浓度垂直结构主要出现在春季,总占比为85%.
结合国内同类O3垂直分布特征和卫星再分析资料评估的研究成果,发现部分结论不仅仅适用于粤港澳地区.针对O3垂直分布特征研究,对比台北、厦门等地探空站点的O3分布特征[20],广东福建等东南部沿海省份同属东亚季风气候区,当地O3垂直浓度均呈现相似的分布模式;针对卫星再分析资料适用性评估,对比各地的评估结论[38-39],卫星和再分析资料均存在局部高度处差异较大的共性问题,尤其在对流层低层区域,同时AIRS臭氧产品在北京地区700~300hPa高度也存在臭氧高估的情况,但整体都与探空结果较为接近,总体来看AIRS和ERA5资料对于研究中国华南区域对流层内臭氧结构的时空变化还是有较好的参考意义.
4.1 粤港澳探空站点O3浓度垂直分布季节性差异较为显著,春夏冬季呈单峰分布结构,秋季呈双峰分布结构.各探空站点间O3浓度差异较小,清远、河源、汕头、阳江与香港站点探测时段O3廓线年平均偏差分别为11.0%、1.6%、0.6%、-3.2%.
4.2 对流层内AIRS、ERA5与探空数据的Rad值为24%和26%,r值为0.77和0.75,总体上AIRS卫星资料略优于ERA5再分析资料.AIRS和ERA5数据质量存在明显的季节差异,秋冬季评估结果优于春夏季.850hPa以下,AIRS和ERA5数据质量均较差,Rad平均值分别为31.6%和40.9%,r平均值分别为0.34和-0.15,AIRS产品优于ERA5产品.850~ 200hPa产品评估结果明显优于850hPa以下的评估结果,各季节Rad平均值分别介于16.5%~25.8%和15.1%~25.7%之间,r平均值分别介于0.47~0.75和0.23~0.74之间.200hPa以上,两套数据的评估结果转差.整体上看,850hPa以上AIRS与ERA5产品各有优势,AIRS产品的相关系数高于ERA5,但AIRS产品的Rad值较大.
4.3 利用SOM分型方法,将O3垂直分布分为5型,其中1型2型为双峰型结构,4型5型归为无峰结构,3型为双峰型向无峰型的过度结构,1~5型占比分别为24.7%、18.7%、16.6%、13.8%和26.2%.在200~100hPa,各分布型下AIRS与ERA5资料质量差异相对较小,而在200hPa以下,5种分布型下的数据质量差异较大.200hPa以下,AIRS与ERA5资料在1型分布结构下Rad平均值最小(分别为19.6%和18.9%),r平均值最高(分别为0.58和0.38);2型和3型分布结构则明显较差,Rad平均值均高于30%,r平均值均低于0.22.1型主要出现在秋季和冬季,出现频率分别为43%和61%,2型和3型主要出现在夏季,总占比为66%,4型和5型主要出现在春季,总占比为85%.
  • 广东省基础与应用基础研究基金项目(2023A1515110536)
  • 广东省科技计划项目(2024B1212040006)
  • 广东省重点研发计划项目(2020B1111360003)
  • 中国气象局青年创新团队项目(CMA2023QN13)
  • 广东省气象局软科学项目(Z202304)
  • 广东省气象局科学技术研究项目(GRMC2022Q10)
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2025年第45卷第4期
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  • 接收时间:2024-10-08
  • 首发时间:2026-03-19
  • 出版时间:2025-04-20
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  • 收稿日期:2024-10-08
基金
广东省基础与应用基础研究基金项目(2023A1515110536)
广东省科技计划项目(2024B1212040006)
广东省重点研发计划项目(2020B1111360003)
中国气象局青年创新团队项目(CMA2023QN13)
广东省气象局软科学项目(Z202304)
广东省气象局科学技术研究项目(GRMC2022Q10)
作者信息
    1.广东省生态气象中心(珠三角环境气象预报预警中心),广东 广州 510640
    2.广东省南岭森林大气环境与碳中和野外科学观测研究站,广东 广州 511443
    3.广东省生态环境监测中心,国家环境保护区域空气质量监测重点实验室,广东省环境保护大气二次污染研究重点实验室,广东 广州 510308

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2种不同金属材料的力学参数

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Genus
种数
Number of
species
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species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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