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Evaluating the Performance of a Regional-Scale Photochemical Modelling System: Part I Ozone Predictions

机译:评估区域规模的光化学建模系统的性能:第一部分臭氧预测

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摘要

We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts.
机译:我们对社区多尺度空气质量(CMAQ)建模系统和PSU / NCAR气象模型以及新的空气质量数字排放模型(MNEQA)的季节性表现进行了详细评估。该组合系统在西班牙东北部经常以较高的分辨率(水平分辨率为3 km,时间分辨率为1 h)模拟空气质量,那里经常发生臭氧污染问题。从2009年5月至2009年9月的两个时期内收集的广泛数据库用于评估气象模拟和化学产品。我们的结果表明,该模型可以准确再现每小时在空气质量站测得的每小时以及1小时和8小时的最大臭氧表面浓度,因为统计值不超过EPA和EU的建议。但是,为了进一步提高预测准确性,基于10天的可用比较,应用了三种简单的偏差调整技术分别表示减法(MS),比率调整(RA)和混合预测(HF)。结果表明,尽管所有偏差调整技术都显着降低了臭氧预报中的系统误差,但MS技术的性能优于RA或HF。

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