首页|基于数值模式与客观方法的辽宁地区空气质量预报检验分析

基于数值模式与客观方法的辽宁地区空气质量预报检验分析

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
为检验数值模式和客观方法的空气质量产品预报能力，基于中国气象科学研究院(简称气科院，下同)CUACE模式、中国气象局沈阳大气环境研究所(简称沈阳大气所，下同)CUACE模式和中央气象台(简称中央台，下同)空气质量客观预报方法的产品，利用辽宁地区 14个地市大气污染物质量浓度地面观测资料，对 2019年 1月至2021年 4月各家预报产品在辽宁地区的预报效果进行检验。结果表明:中央台的环境空气质量指数(Air Quality Index，AQI)预报偏大，气科院和沈阳大气所偏小;各家的PM2。5 和PM10 预报均偏小，但中央台的误差最小;各家的O3 预报均偏大，气科院的预报误差最小。各家产品对PM2。5 和O3 浓度变化趋势的预报能力较高，对AQI范围的预报能力是强于AQI等级的。各家产品预报的PM2。5 质量浓度离散度和预报偏差最小，TS评分最高;大气污染物浓度和AQI在辽宁东南部的预报可靠性最高、中部地区最差。三家产品相比，中央台在辽宁地区的预报能力最强，对AQI、大气污染物浓度和首要污染物的预报TS评分均为最高，特别是在有(或无明显首要污染物)特定大气污染物对应的季节，预报更具有指导性。沈阳大气所的本地化CUACE模式对于大气污染物浓度和AQI的预报能力显著提高。
Verification analysis of air quality forecast based on numerical models and objective methods in Liaoning
To test the numerical models and objective methods of air quality forecast ability,based on the product of the CUACE model of Chinese Academy of Meteorological Sciences(AMS),the CUACE model of Shenyang Institute of Atmospheric Environment of China Meteorological Administration(SY-CMA)and the National Meteorological Center(NMC)air quality objective prediction method,the ground observation data of air pollutant mass concentration in 14 cities in Liaoning were used to test the forecast effects of various forecast products in Liaoning from January 2019 to April 2021.The results showed that the Air Quality Index(AQI)of NMC was larger than the real data,but the AQI of AMS and SY-CMA were smaller.The PM2.5 and PM10 mass concentrations of each forecast product were relatively small,but the prediction error of NMC was the smallest.The O3 mass concentration of each forecast product was relatively large,and the prediction error of AMS was the smallest.The prediction ability of each forecast product for the changing trend of PM2.5 and O3 mass concentration was relatively high,and the prediction ability of the AQI-range was stronger than the AQI level.The products have smaller dispersion and deviation of PM2.5 mass concentration,and the TS score is the highest.The prediction reliability of air pollutant concentration and AQI was the highest in southeast Liaoning and the worst in central Liaoning.Compared with the three products,NMC had the strongest forecasting ability in Liaoning,with the highest forecast TS scores for AQI,air pollutant concentration,and primary pollutants,especially in the seasons corresponding to specific primary pollutants(or without obvious primary pollutants),which was more instructive.The prediction ability of the localized CUACE model of SY-CMA for atmospheric pollutant concentration and AQI was significantly improved.

forecast verificationCUACE-Haze/Fog modeobjective forecastAQIprimary pollutantTS score

张宸赫、王东东、李晓岚、杜傢义、赵天良

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辽宁省气象台,沈阳 110166

中国气象局沈阳大气环境研究所,沈阳 110166

南京信息工程大学,中国气象局气溶胶与云降水重点开放实验室,南京 210044

预报检验 CUACE模式 客观预报 空气质量 首要污染物 TS评分

辽宁省自然科学基金辽宁省气象局科研重点项目环渤海区域科技协同创新基金中央级公益性科研院所基本科研业务费专项重点项目

2020-MS-350202004QYXM2021032021SYIAEZD2

2024

10.16803/j.cnki.issn.1004-6216.202212027

环境保护科学
沈阳环境科学研究院

环境保护科学

CSTPCD
影响因子：0.469
ISSN：1004-6216
年,卷(期)：2024.50(1)
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