Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models

Youhua Tang, Gregory R. Carmichael, Narisara Thongboonchoo, Tianfeng Chai, Larry W. Horowitz, Robert B. Pierce, Jassim A. Al-Saadi, Gabriele Pfister, Jeffrey M. Vukovich, Melody A. Avery, Glen W. Sachse, Thomas B. Ryerson, John S. Holloway, Elliot L. Atlas, Frank M. Flocke, Rodney J. Weber, L. Gregory Huey, Jack E. Dibb, David G. Streets, William H. Brune

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The sensitivity of regional air quality model to various lateral and top boundary conditions is studied at 2 scales: a 60 km domain covering the whole USA and a 12 km domain over northeastern USA. Three global models (MOZART-NCAR, MOZART-GFDL and RAQMS) are used to drive the STEM-2K3 regional model with time-varied lateral and top boundary conditions (BCs). The regional simulations with different global BCs are examined using ICARTT aircraft measurements performed in the summer of 2004, and the simulations are shown to be sensitive to the boundary conditions from the global models, especially for relatively long-lived species, like CO and O3. Differences in the mean CO concentrations from three different global-model boundary conditions are as large as 40 ppbv, and the effects of the BCs on CO are shown to be important throughout the troposphere, even near surface. Top boundary conditions show strong effect on O3 predictions above 4 km. Over certain model grids, the model's sensitivity to BCs is found to depend not only on the distance from the domain's top and lateral boundaries, downwind /upwind situation, but also on regional emissions and species properties. The near-surface prediction over polluted area is usually not as sensitive to the variation of BCs, but to the magnitude of their background concentrations. We also test the sensitivity of model to temporal and spatial variations of the BCs by comparing the simulations with time-varied BCs to the corresponding simulations with time-mean and profile BCs. Removing the time variation of BCs leads to a significant bias on the variation prediction and sometime causes the bias in predicted mean values. The effect of model resolution on the BC sensitivity is also studied.

Original languageEnglish (US)
Article numberD10S18
JournalJournal of Geophysical Research Atmospheres
Issue number10
StatePublished - May 27 2007

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Oceanography
  • Forestry
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Space and Planetary Science
  • Earth and Planetary Sciences (miscellaneous)
  • Palaeontology


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