Preprints
https://doi.org/10.5194/egusphere-2023-1089
https://doi.org/10.5194/egusphere-2023-1089
09 Jun 2023
 | 09 Jun 2023

Parameterized minimum eddy diffusivity in WRF-Chem(v3.9.1.1) for improving PM2.5 simulation in the stable boundary layer over eastern China

Wen Lu, Bin Zhu, Shuqi Yan, Jie Li, and Zifa Wang

Abstract. Weak turbulence often occurs during heavy pollution events in eastern China. However, existing mesoscale models cannot accurately simulate turbulent diffusion under weakened turbulence, particularly under the nocturnal stable boundary layer (SBL), often leading to significant turbulent diffusivity underestimation and surface aerosol simulation overestimation. In this study, based on the Weather Research and Forecasting model coupled with the Chemistry model (WRF-Chem 3.9.1), a new parameterization of minimum turbulent diffusivity (Kzmin) is tested and applied in PM2.5 simulations in eastern China under SBL conditions. Sensitivity experiments show that there are different value ranges of available Kzmin over the northern (0.8 to 1.3 m2·s-1) and southern (1.0 to 1.5 m2·s-1) regions of East China. The geographically related Kzmin could be parameterized by means of two factors: sensible heat flux (H) and latent heat flux (LE), which also exhibited a regional difference related to the climate and underlying surface. The revised Kzmin scheme obviously enhanced the turbulent diffusion (north: 0.88 m2·s-1, south: 1.17 m2·s-1 on average) under the SBL, simultaneously improving the PM2.5 simulations, with the PM2.5 relative bias decreasing from 43.0 % to 15.6 % on the surface. The improvement in the mean bias of the surface simulation was more noticeable in the north (54.01 to 3.79 ug·m-3) than in the south (37.05 to 17.99 ug·m-3). It also increased the PM2.5 concentration in the upper SBL. Furthermore, we discussed the physical relationship between Kzmin and two factors. Kzmin was inversely correlated with sensible heat flux (negative) and latent heat flux (positive) in the SBL. Process analysis showed that vertical mixing is the key process to improve PM2.5 simulations on the surface in the revised scheme. The increase in the PM2.5 concentration in the upper SBL was attributed to vertical mixing, advection, and aerosol chemistry. This study highlights the importance of improving turbulent diffusion in current mesoscale models under the SBL and has great significance for aerosol simulation research under heavy air pollution events.

Wen Lu, Bin Zhu, Shuqi Yan, Jie Li, and Zifa Wang

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1089', Anonymous Referee #1, 29 Jun 2023
    • AC1: 'Reply on RC1', Wen Lu, 02 Sep 2023
  • RC2: 'Comment on egusphere-2023-1089', Anonymous Referee #2, 29 Jun 2023
    • AC2: 'Reply on RC2', Wen Lu, 02 Sep 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1089', Anonymous Referee #1, 29 Jun 2023
    • AC1: 'Reply on RC1', Wen Lu, 02 Sep 2023
  • RC2: 'Comment on egusphere-2023-1089', Anonymous Referee #2, 29 Jun 2023
    • AC2: 'Reply on RC2', Wen Lu, 02 Sep 2023
Wen Lu, Bin Zhu, Shuqi Yan, Jie Li, and Zifa Wang
Wen Lu, Bin Zhu, Shuqi Yan, Jie Li, and Zifa Wang

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Short summary
Parameterized the minimum turbulent diffusivity (Kzmin) by sensible heat flux and latent heat flux and embedded it into the WRF-Chem model. New scheme improved the underestimation of turbulence diffusion underestimation and overestimation of surface PM2.5 under stable boundary layer simulation over eastern China. The physical relationship between Kzmin and two factors was discussed. Process analysis showed that vertical mixing is the key process to improve surface PM2.5 simulations.