Observational operator for fair model evaluation with ground NO2 measurements
Abstract
Measurements collected from ground monitoring stations have gained popularity as a valuable data source for evaluating numerical models and correcting model errors through data assimilation. The penalty quantified by simulation minus observations drives both model evaluation and assimilation. However, the penal forces are challenged by the existence of a spatial-scale disparity between model simulations and observations. Chemical transport models (CTMs) divide the atmosphere into grid cells, providing a structured way to simulate atmospheric processes. However, their spatial resolution often does not match the limited coverage of in situ measurements, especially for short-lived air pollutants. Within a broad grid cell, air pollutant concentrations can exhibit significant heterogeneity due to their rapid generation and dissipation. Ground observations with traditional methods (including "nearest search"and "grid mean") are less representative when compared to model simulations. This study develops a new land-use-based representative (LUBR) observational operator to generate spatially representative gridded observations for model evaluation. It incorporates high-resolution urban-rural land use data to address intra-grid variability. The LUBR operator has been validated to consistently provide insights that align with satellite Ozone Monitoring Instrument (OMI) measurements. It is an effective solution to accurately quantify these spatial-scale mismatches and further resolve them via assimilation. Model evaluations with 2015-2017 NO2 measurements in the study area demonstrate that biases and errors differed substantially when the LUBR and other operators were used, respectively. The results highlight the importance of considering fine-scale urban-rural differences when comparing models and observations, especially for short-lived pollutants like NO2. Copyright: © 2024 Li Fang et al.
Authors 11
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China
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Netherlands Organisation for Applied Scientific Research
Affiliation as printed
TNO , Department of Climate , Air and Sustainability , Utrecht , the Netherlands
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China
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China Meteorological Administration
Affiliation as printed
CMA Earth System Modeling and Prediction Centre (CEMC) , China Meteorological Administration , Beijing , China
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China
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Leiden University · Delft University of Technology
Affiliation as printed
Delft Institute of Applied Mathematics , Delft University of Technology , Delft , the Netherlands
Institute of Environmental Sciences , Leiden University , Leiden , the Netherlands
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Southern University of Science and Technology
Affiliation as printed
School of Environmental Science and Engineering , Southern University of Science and Technology , Shenzhen , China
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Nanjing University of Information Science and Technology
Affiliation as printed
Joint International Research Laboratory of Climate and Environment Change , Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control , Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology , School of Environmental Science and Engineering , Nanjing University of Information Science and Technology , Nanjing , Jiangsu , China