Evaluation of tropospheric ozone and ozone precursors in simulations from the HTAPII and CCMI model intercomparisons – a focus on the Indian subcontinent
Authors: Hakim Zainab Q. , Archer-Nicholls Scott , Beig Gufran , Folberth Gerd A. , Sudo Kengo , Abraham Nathan Luke , Ghude Sachin , Henze Daven K. , Archibald Alexander T. 
Published: May 2019

Abstract. Here we present results from an evaluation of model simulations from the
International Hemispheric Transport of Air Pollution Phase II (HTAPII) and
Chemistry Climate Model Initiative (CCMI) model inter-comparison projects
against a comprehensive series of ground-based, aircraft and satellite
observations of ozone mixing ratios made at various locations across India.
The study focuses on the recent past (observations from 2008 to 2013, models
from 2009–2010) as this is most pertinent to understanding the health
impacts of ozone. To our understanding this is the most comprehensive
evaluation of these models' simulations of ozone across the Indian
subcontinent to date. This study highlights some significant successes and
challenges that the models face in representing the oxidative chemistry of
the region. The multi-model range in area-weighted surface ozone over the Indian
subcontinent is 37.26–56.11 ppb, whilst the population-weighted range is
41.38–57.5 ppb. When compared against surface observations from the
Modelling Atmospheric Pollution and Networking (MAPAN) network of eight
semi-urban monitoring sites spread across India, we find that the models tend
to simulate higher ozone than that which is observed. However, observations
of NOx and CO tend to be much higher than modelled mixing
ratios, suggesting that the underlying emissions used in the models do not
characterise these regions accurately and/or that the resolution of the
models is not adequate to simulate the photo-chemical environment of these
surface observations. Empirical orthogonal function (EOF) analysis is used in
order to identify the extent to which the models agree with regards to the
spatio-temporal distribution of the tropospheric ozone column, derived using
OMI-MLS observations. We show that whilst the models agree with the spatial
pattern of the first EOF of observed tropospheric ozone column, most of the
models simulate a peak in the first EOF seasonal cycle represented by
principle component 1, which is later than the observed peak. This suggests a
widespread systematic bias in the timing of emissions or some other unknown
seasonal process. In addition to evaluating modelled ozone mixing ratios, we explore modelled
emissions of NOx, CO, volatile organic compounds (VOCs) and the ozone response to the
emissions. We find a high degree of variation in emissions from
non-anthropogenic sources (e.g. lightning NOx and biomass
burning CO) between models. Total emissions of NOx and CO
over India vary more between different models in the same model intercomparison project (MIP) than the same
model used in different MIPs, making it impossible to diagnose whether
differences in modelled ozone are due to emissions or model processes. We
therefore recommend targeted experiments to pinpoint the exact causes of
discrepancies between modelled and observed ozone and ozone precursors for
this region. To this end, a higher density of long-term monitoring sites
measuring not only ozone but also ozone precursors including speciated VOCs,
located in more rural regions of the Indian subcontinent, would enable
improvements in assessing the biases in models run at the resolution found in
HTAPII and CCMI.