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云下湿清除作用对上海PM_(2.5)业务数值预报的影响

Effect of blow-cloud wet scavenging on operational numerical forecast of PM_(2.5) over Shanghai
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摘要 在华东区域大气环境数值预报系统中耦合气溶胶云下湿清除参数化方案,于2022年开展了区域空气质量业务数值预报,并以原业务系统回报作为对照,分析了业务预报对上海地区PM_(2.5)预报能力的改进效果.结果表明,不同时效的业务预报性能总体相当,预报效果指标优于对照试验并减弱了偏高程度和偏差分布的“右偏”特征;业务预报的PM_(2.5)浓度随降水增强的下降趋势与观测接近,基本消除了不同降水条件对预报效果的影响;2022年PM_(2.5)等级预报准确率达80%,较对照结果提升了6.3个百分点,其中雨日提升(8.0个百分点)更显著并通过改善化学初始或输送条件促进了非雨日的提升.同时也发现,业务预报仍存在一定系统性偏高,可应用数值预报释用等技术进一步提升预报效果. Using the upgraded Regional Atmospheric Environmental Modeling System for eastern China(RAEMS) implemented with a parameterization scheme for aerosol blow-cloud wet scavenging,the operational forecast of regional air quality in 2022 was carried out and the improvement compared to that of the previous operational RAEMS(control test) was analyzed for PM_(2.5) prediction over Shanghai.The results showed that the operational forecast has overall comparable prediction performance in different forecast lengths,which is better than that of the control test and decreased the extent of overestimation and positive forecast biases.The declining trend of PM_(2.5) concentration with an increase of precipitation in the operational forecast is close to that of the observed,indicating that the shortage of precipitation condition decreasing prediction capability which exists in the control test,is basically rectified.As a result,the forecast accuracy on PM_(2.5) index grades reached 80%,which grew by 6.3 percentage points to the control run,and that in rainy days grew a higher score by 8.0 percentage points which further promoted the increase in non-rainy days by improving their chemical initial or transportation conditions.At the same time,the over-forecast of PM_(2.5) concentration still exists in the operational forecast,suggesting the importance and necessity of applications of model output statistic techniques to provide better PM_(2.5) forecast.
作者 周广强 毛卓成 瞿元昊 彭丽 ZHOU Guangqiang;MAO Zhuocheng;QU Yuanhao;PENG Li(Yangtze River Delta Center for Environmental Meteorology Prediction and Warning,Shanghai 200030;Shanghai Key Laboratory of Meteorology and Health,Shanghai Meteorological Service,Shanghai 200030)
出处 《环境科学学报》 CAS CSCD 北大核心 2024年第7期410-418,共9页 Acta Scientiae Circumstantiae
基金 国家重点研发计划项目(No.2016YFC0201900) 上海市自然科学基金资助项目(No.21ZR1469400) 上海市科技计划项目(No.20dz1204000)。
关键词 PM_(2.5) 数值预报 湿清除 降水 WRF-Chem PM2.5 numerical prediction wet scavenging precipitation WRF-Chem
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