Home > Publications database > Seasonal and interannual variability of carbon monoxide based on MOZAIC observations, MACC reanalysis, and model simulations over an urban site in India |
Journal Article | FZJ-2014-04549 |
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2014
Union
Washington, DC
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Please use a persistent id in citations: http://hdl.handle.net/2128/16096 doi:10.1002/2013JD021425
Abstract: The spatial and temporal variations of carbon monoxide (CO) are analyzed over a tropical urban site, Hyderabad (17°27′N, 78°28′E) in central India. We have used vertical profiles from the Measurement of ozone and water vapor by Airbus in-service aircraft (MOZAIC) aircraft observations, Monitoring Atmospheric Composition and Climate (MACC) reanalysis, and two chemical transport model simulations (Model for Ozone And Related Tracers (MOZART) and MRI global Chemistry Climate Model (MRI-CCM2)) for the years 2006–2008. In the lower troposphere, the CO mixing ratio showed strong seasonality, with higher levels (>300 ppbv) during the winter and premonsoon seasons associated with a stable anticyclonic circulation, while lower CO values (up to 100 ppbv) were observed in the monsoon season. In the planetary boundary layer (PBL), the seasonal distribution of CO shows the impact of both local meteorology and emissions. While the PBL CO is predominantly influenced by strong winds, bringing regional background air from marine and biomass burning regions, under calm conditions CO levels are elevated by local emissions. On the other hand, in the free troposphere, seasonal variation reflects the impact of long-range transport associated with the Intertropical Convergence Zone and biomass burning. The interannual variations were mainly due to transition from El Niño to La Niña conditions. The overall modified normalized mean biases (normalization based on the observed and model mean values) with respect to the observed CO profiles were lower for the MACC reanalysis than the MOZART and MRI-CCM2 models. The CO in the PBL region was consistently underestimated by MACC reanalysis during all the seasons, while MOZART and MRI-CCM2 show both positive and negative biases depending on the season.
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