Since 2017, the operational high-resolution air quality forecasting system FORAIR_IT, developed and maintained by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, has been providing three-day forecasts of concentrations of atmospheric pollutants over Europe and Italy, on a daily basis, with high spatial resolution (20 km on Europe, 4 km on Italy). The system is based on the Atmospheric Modelling System of the National Integrated Assessment Model for Italy (AMS-MINNI), which is a national modelling system evaluated in several studies across Italy and Europe. AMS-MINNI, in its forecasting setup, is presently a candidate model for the Copernicus Atmosphere Monitoring Service’s regional production, dedicated to European-scale ensemble model forecasts of air quality. In order to improve the quality of the meteorological input into the chemical transport model component of FORAIR_IT, several tests were carried out on daily forecasts of NO₂ and O₃ concentrations for January and August 2019 (representative of the meteorological seasons of winter and summer, respectively). The aim was to evaluate the sensitivity to the meteorological input in NO₂ and O₃ concentration forecasting. More specifically, the Weather Research and Forecasting model (WRF) was tested to potentially improve the meteorological driver with respect to the Regional Atmospheric Modelling System (RAMS), which is currently embedded in FORAIR_IT. In this work, the WRF chain is run in several setups, changing the parameterization of several micrometeorological variables (snow, mixing height, albedo, roughness length, soil heat flux + friction velocity, Monin–Obukhov length), with the main objective being to take advantage of WRF’s consistent physics in the calculation of both mesoscale variables and micrometeorological parameters for air quality simulations. Daily forecast concentrations produced by the different meteorological model configurations are compared to the available measured concentrations, showing the general good performance of WRF-driven results, even if performance skills are different according to the single meteorological configuration and to the pollutant type. WRF-driven forecasts clearly improve the model reproduction of the temporal variability of concentrations, while the bias of O₃ is higher than in the RAMS-driven configuration. The results suggest that we should keep testing WRF configurations, with the objective of obtaining a robust improvement in forecast concentrations with respect to RAMS-driven forecasts.

中文翻译：

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FORAIR_IT空气质量预报系统对不同气象驾驶员的敏感性的初步测试

自2017年以来，由意大利新技术，能源和可持续经济发展国家局开发和维护的高分辨率运行空气质量预报系统FORAIR_IT一直提供欧洲和意大利的三天大气污染物浓度预测。每天都具有较高的空间分辨率（欧洲20公里，意大利4公里）。该系统基于意大利国家综合评估模型（AMS-MINNI）的大气建模系统，这是一项在意大利和欧洲的多项研究中评估的国家建模系统。AMS-MINNI在其预测设置中，目前是哥白尼大气监测局区域生产的候选模型，致力于欧洲规模的整体空气质量模型预测。2019年1月和8月的₂和O ₃浓度（分别代表冬季和夏季的气象季节）。目的是评估NO ₂和O ₃对气象输入的敏感性浓度预测。更具体地说，已经对天气研究和预报模型（WRF）进行了测试，以相对于当前嵌入FORAIR_IT的区域大气建模系统（RAMS）潜在地改善气象驱动因素。在这项工作中，WRF链以多种设置运行，更改了几个微气象变量（雪，混合高度，反照率，粗糙度长度，土壤热通量+摩擦速度，莫宁-奥布霍夫长度）的参数化，其主要目的是在计算中尺度变量和微气象参数时，利用WRF的一致性物理学来模拟空气质量。将不同气象模型配置产生的每日预测浓度与可用的测量浓度进行比较，即使根据单一的气象配置和污染物类型，性能技能有所不同，也显示出WRF驱动结果的总体良好性能。WRF驱动的预测明显改善了浓度随时间变化的模型再现，而O的偏差₃高于RAMS驱动的配置。结果表明，我们应该继续测试WRF配置，以期相对于RAMS驱动的预测在预测集中度方面获得有力的改善。