Evaluation of WRF-Chem simulated meteorology and aerosols over northern India during the severe pollution episode of 2016

Severe seasonal air pollution events have become frequent over northern India, particularly over the Indo-Gangetic Plain (IGP). These episodic hazes, marked by exceedingly high levels of ambient PM2.5 (particulate matter having an aerodynamic diameter ≤ 2.5 microns), are hazardous for visibility and public health. It is therefore imperative to examine the capabilities of current state-of-the-art coupled meteorology-chemistry models at predicting air quality over this region. We provide a comprehensive evaluation of WRF-Chem (v4.2.1) simulated seasonal meteorology and aerosol chemistry (PM2.5 and its black carbon (BC) component) using a range of ground-based, satellite and reanalysis products, with a focus on the November 2016 haze episode. Daily and diurnal features in simulated 2 m temperature show best agreement followed by relative humidity with overall low biases. Upper air meteorology comparisons with radiosonde observations show excellent model skill in reproducing the vertical temperature gradient (r > 0.95). Both ground and radiosonde observations confirm systematic overestimations in simulated surface wind speeds (by ~ 0.5 – 0.8 m s−1), driven by high nocturnal biases. Modelled PM2.5 concentrations generally compare well with the ground-based measurements in October–November (post-monsoon) but are strongly overestimated (by a factor of 2) in September (monsoon) due to dust constituent. Delhi experiences some of the highest daily mean PM2.5 concentrations within the study region with largest biases during the extreme pollution episode. Dominant anthropogenic components in the modelled PM2.5 in Delhi during the episode include nitrate (~ 25 %), followed by secondary organic aerosols (~ 20 %), and primary organic matter, and elevated BC concentrations. Modelled spatiotemporal PM2.5 and BC compare well with MERRA-2 products. Spatially, high aerosol optical depth (AOD) over the IGP is accurately represented by the model relative to MODIS satellite (r ≥ 0.8), and ground-based AERONET observations (r ≥ 0.69), except during September. Generally, WRF-Chem correctly represents the meteorology during the afternoon and has a reasonable ability to reproduce wind patterns. This (among other factors like imperfect representation of emissions and land use information) plays a key role in dust overestimations in monsoon and anthropogenic aerosol underestimations in post-monsoon owing to enhanced dilution and mixing in the model. Overall, we find the model suitable to understand the aerosol feedbacks on meteorology during extreme pollution events with an improved diurnal characterisation of boundary layer processes and emissions estimates.