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. Here we present results from an evaluation of model simulations from theInternational Hemispheric Transport of Air Pollution Phase II (HTAPII) andChemistry Climate Model Initiative (CCMI) model inter-comparison projectsagainst a comprehensive series of ground-based, aircraft and satelliteobservations of ozone mixing ratios made at various locations across India.The study focuses on the recent past (observations from 2008 to 2013, modelsfrom 2009–2010) as this is most pertinent to understanding the healthimpacts of ozone. To our understanding this is the most comprehensiveevaluation of these models' simulations of ozone across the Indiansubcontinent to date. This study highlights some significant successes andchallenges that the models face in representing the oxidative chemistry ofthe region. The multi-model range in area-weighted surface ozone over the Indiansubcontinent is 37.26–56.11 ppb, whilst the population-weighted range is41.38–57.5 ppb. When compared against surface observations from theModelling Atmospheric Pollution and Networking (MAPAN) network of eightsemi-urban monitoring sites spread across India, we find that the models tendto simulate higher ozone than that which is observed. However, observationsof NOx and CO tend to be much higher than modelled mixingratios, suggesting that the underlying emissions used in the models do notcharacterise these regions accurately and/or that the resolution of themodels is not adequate to simulate the photo-chemical environment of thesesurface observations. Empirical orthogonal function (EOF) analysis is used inorder to identify the extent to which the models agree with regards to thespatio-temporal distribution of the tropospheric ozone column, derived usingOMI-MLS observations. We show that whilst the models agree with the spatialpattern of the first EOF of observed tropospheric ozone column, most of themodels simulate a peak in the first EOF seasonal cycle represented byprinciple component 1, which is later than the observed peak. This suggests awidespread systematic bias in the timing of emissions or some other unknownseasonal process. In addition to evaluating modelled ozone mixing ratios, we explore modelledemissions of NOx , CO, volatile organic compounds (VOCs) and the ozone response to theemissions. We find a high degree of variation in emissions fromnon-anthropogenic sources (e.g. lightning NOx and biomassburning CO) between models. Total emissions of NOx and COover India vary more between different models in the same model intercomparison project (MIP) than the samemodel used in different MIPs, making it impossible to diagnose whetherdifferences in modelled ozone are due to emissions or model processes. Wetherefore recommend targeted experiments to pinpoint the exact causes ofdiscrepancies between modelled and observed ozone and ozone precursors forthis region. To this end, a higher density of long-term monitoring sitesmeasuring not only ozone but also ozone precursors including speciated VOCs,located in more rural regions of the Indian subcontinent, would enableimprovements in assessing the biases in models run at the resolution found inHTAPII and CCMI.

atmospheric chemistry and physics

Evaluation of tropospheric ozone and ozone precursors in simulations from the HTAPII and CCMI model intercomparisons – a focus on the Indian subcontinent