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

Research output: Contribution to journalArticle

56 Citations (Scopus)

Abstract

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 C: Oceans
Volume112
Issue number10
DOIs
StatePublished - May 27 2007

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air quality
Air quality
boundary condition
Boundary conditions
boundary conditions
prediction
predictions
Carbon Monoxide
sensitivity
chemical
simulation
Troposphere
airborne survey
troposphere
aircraft
summer

ASJC Scopus subject areas

  • Oceanography
  • Geochemistry and Petrology
  • Geophysics
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Atmospheric Science
  • Astronomy and Astrophysics

Cite this

Influence of lateral and top boundary conditions on regional air quality prediction : A multiscale study coupling regional and global chemical transport models. / Tang, Youhua; Carmichael, Gregory R.; Thongboonchoo, Narisara; Chai, Tianfeng; Horowitz, Larry W.; Pierce, Robert B.; Al-Saadi, Jassim A.; Pfister, Gabriele; Vukovich, Jeffrey M.; Avery, Melody A.; Sachse, Glen W.; Ryerson, Thomas B.; Holloway, John S.; Atlas, Elliot L; Flocke, Frank M.; Weber, Rodney J.; Huey, L. Gregory; Dibb, Jack E.; Streets, David G.; Brune, William H.

In: Journal of Geophysical Research C: Oceans, Vol. 112, No. 10, D10S18, 27.05.2007.

Research output: Contribution to journalArticle

Tang, Y, Carmichael, GR, Thongboonchoo, N, Chai, T, Horowitz, LW, Pierce, RB, Al-Saadi, JA, Pfister, G, Vukovich, JM, Avery, MA, Sachse, GW, Ryerson, TB, Holloway, JS, Atlas, EL, Flocke, FM, Weber, RJ, Huey, LG, Dibb, JE, Streets, DG & Brune, WH 2007, 'Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models', Journal of Geophysical Research C: Oceans, vol. 112, no. 10, D10S18. https://doi.org/10.1029/2006JD007515
Tang, Youhua ; Carmichael, Gregory R. ; Thongboonchoo, Narisara ; Chai, Tianfeng ; Horowitz, Larry W. ; Pierce, Robert B. ; Al-Saadi, Jassim A. ; Pfister, Gabriele ; Vukovich, Jeffrey M. ; Avery, Melody A. ; Sachse, Glen W. ; Ryerson, Thomas B. ; Holloway, John S. ; Atlas, Elliot L ; Flocke, Frank M. ; Weber, Rodney J. ; Huey, L. Gregory ; Dibb, Jack E. ; Streets, David G. ; Brune, William H. / Influence of lateral and top boundary conditions on regional air quality prediction : A multiscale study coupling regional and global chemical transport models. In: Journal of Geophysical Research C: Oceans. 2007 ; Vol. 112, No. 10.
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abstract = "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.",
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AU - Carmichael, Gregory R.

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AU - Chai, Tianfeng

AU - Horowitz, Larry W.

AU - Pierce, Robert B.

AU - Al-Saadi, Jassim A.

AU - Pfister, Gabriele

AU - Vukovich, Jeffrey M.

AU - Avery, Melody A.

AU - Sachse, Glen W.

AU - Ryerson, Thomas B.

AU - Holloway, John S.

AU - Atlas, Elliot L

AU - Flocke, Frank M.

AU - Weber, Rodney J.

AU - Huey, L. Gregory

AU - Dibb, Jack E.

AU - Streets, David G.

AU - Brune, William H.

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N2 - 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.

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