TY - GEN
T1 - AQMEII PHASE 4, Dissecting the Deposition Process in Regional Scale Models, Preliminary Results
AU - Kioutsioukis, I.
AU - Makar, P.
AU - Cheung, P.
AU - Hodzic, A.
AU - Ryu, Young Hee
AU - Lupascu, A.
AU - Butler, T.
AU - Jose, R. S.
AU - Perez-Camanyo, J. L.
AU - Kranenburg, R.
AU - Hogrefe, Christian
AU - Bash, Jesse
AU - Pleim, Jonathan
AU - Schwede, Donna
AU - Alyuz, U.
AU - Momoh, K.
AU - Sokhi, R.
AU - Holmes, C.
AU - Nowell, H.
AU - Bellasio, R.
AU - Bianconi, R.
AU - Clifton, O.
AU - Galmarini, S.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - In this study, we present the first evaluation of grid model results of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII-4). The focus of this phase is deposition, a topic long neglected by the atmospheric modelling community in intercomparison studies that this time has been tackled with a detail that is unparalleled in regional scale modelling. Four modeling systems were run in different configurations using common anthropogenic, biomass burning, and lightning emissions, for the years 2010 and 2016 for North America (NA), and 2009 and 2010 for Europe (EU). The ensemble members used their own driving meteorology and biogenic emissions data in these simulations. Using a large database of monitoring data matched to model output, this study covers the operational evaluation of modelled concentration fields, which is of paramount importance prior to the analysis of the deposition. The PM10 concentrations were generally underestimated in both continents, yielding average normalized RMSE 0.5 in EU and 0.6 in NA. Model performance was better for the overestimated O3 concentrations, with an average normalized RMSE of 0.2. Work in progress focuses on an in-depth attribution of the errors (e.g. missing emission sources, mis-represented processes, meteorological biases) with the ultimate goal of assessing the impact these sources of error on the deposition schemes and calculated deposition fluxes.
AB - In this study, we present the first evaluation of grid model results of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII-4). The focus of this phase is deposition, a topic long neglected by the atmospheric modelling community in intercomparison studies that this time has been tackled with a detail that is unparalleled in regional scale modelling. Four modeling systems were run in different configurations using common anthropogenic, biomass burning, and lightning emissions, for the years 2010 and 2016 for North America (NA), and 2009 and 2010 for Europe (EU). The ensemble members used their own driving meteorology and biogenic emissions data in these simulations. Using a large database of monitoring data matched to model output, this study covers the operational evaluation of modelled concentration fields, which is of paramount importance prior to the analysis of the deposition. The PM10 concentrations were generally underestimated in both continents, yielding average normalized RMSE 0.5 in EU and 0.6 in NA. Model performance was better for the overestimated O3 concentrations, with an average normalized RMSE of 0.2. Work in progress focuses on an in-depth attribution of the errors (e.g. missing emission sources, mis-represented processes, meteorological biases) with the ultimate goal of assessing the impact these sources of error on the deposition schemes and calculated deposition fluxes.
UR - http://www.scopus.com/inward/record.url?scp=105002028532&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-70424-6_11
DO - 10.1007/978-3-031-70424-6_11
M3 - Conference contribution
AN - SCOPUS:105002028532
SN - 9783031704239
T3 - Springer Proceedings in Complexity
SP - 89
EP - 96
BT - Air Pollution Modeling and Its Application XXIX
A2 - Mensink, Clemens
A2 - Mathur, Rohit
A2 - Arunachalam, Saravanan
PB - Springer Science and Business Media B.V.
T2 - 39th International Technical Meeting on Air Pollution Modeling and its Application, ITM 2023
Y2 - 22 May 2023 through 26 May 2023
ER -