Limitations of Global models in Representing Arctic Tropospheric Ozone and its Precursors
Monday, 14 December 2015
Poster Hall (Moscone South)
To have confidence in model predictions of tropospheric pollutants in the Arctic under future conditions, the models need to reproduce current observations. The POLARCAT Model Intercomparison Project (POLMIP) evaluated nine global and two regional models using the observations of the POLARCAT aircraft experiments in 2008, as well as ground-based and satellite observations. These comparisons indicate a significant underestimate of emissions of CO and hydrocarbons in the Northern Hemisphere (NH), as well as large differences between models in OH concentrations and NOy (PAN vs HNO3) partitioning. This presentation will summarize the findings of the POLMIP exercise, as well as evaluations of additional model results for on-going intercomparison activities with several long-term observational datasets. The NOAA/GMD network of surface in situ observations of O3, CO and hydrocarbons provide long records at sites in the Arctic and throughout the NH. FTIR profile or column amounts of CO, C2H6, C2H4, C2H2, and other compounds are available at northern mid-latitude and Arctic sites (e.g., Thule, Eureka, Toronto, etc.) as part of the Network for the Detection of Atmospheric Composition Change (NDACC). The UC-Irvine Blake group has observed numerous hydrocarbons each season for several decades along the latitudinal extent of the Pacific Ocean, providing a global background record of ethane and propane. These three long-term records are used to evaluate model simulations provided for the IGAC/SPARC Chemistry-Climate Model Initiative (CCMI) and the Task Force on Hemispheric Transport of Air Pollution (HTAP, phase 2), focusing on the model representations of ozone and its precursors in the northern mid and high latitudes. The possible sources of model errors (e.g., emissions, transport and/or chemical processing) will be discussed. Conclusions on what additional measurements (which compounds, where and how frequently) are needed to better constrain and improve global chemistry models will also be presented.