A mixed layer height parameterization in a 3-D chemical transport model: Implications for gas and aerosol simulations
Year: 2024
Type: article
Abstract: Vertical mixing within the planetary boundary layer (PBL) is crucial for determining surface-level pollutant concentrations. However, standard PBL schemes in chemical transport models (CTMs) often fail to adequately define the upper bounds of vertical mixing, particularly at night. This limitation frequently results in overestimated nocturnal concentrations of pollutants near the surface. To address this issue, we propose a parameterization of mixed layer height (MLH) derived from the Yonsei University (YSU) PBL scheme and thoroughly evaluate it by comparing simulations with various observations. We utilized the Weather Research and Forecasting model coupled with GEOS-Chem (WRF-GC) to simulate gas and aerosol distributions over South Korea during the Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) campaign in 2021. The WRF-GC simulations incorporating the MLH parameterization improved the excessive titration of O3 and the overproduction of HNO3 and NO3- in the model. Consequently, the model performances in gaseous and aerosol simulations showed a better agreement with observations, with changes in normalized mean biases (NMBs) of NOX (from 50% to -27%), O3 (from -49% to -28%), NO3- (from 126% to 91%), NH4+ (from 113% to 85%), BC (from 322% to 135%), and PM2.5 (from 58% to 28%).
Institutions: Seoul National University, National Oceanic and Atmospheric Administration, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, NOAA Physical Sciences Laboratory, NOAA Earth System Research Laboratory, Korean Association Of Science and Technology Studies, Korea Institute of Science and Technology, Harvard University, Southern University of Science and Technology
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: hybrid
Estimated APC paid: $3,990
Award: G8647574223
OpenAlex ID: W4403317501
