Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation

Marcelo Mena-Carrasco, Youhua Tang, Gregory R. Carmichael, Tianfeng Chai, Narisara Thongbongchoo, J. Elliott Campbell, Sarika Kulkarni, Larry Horowitz, Jeffrey Vukovich, Melody Avery, William Brune, Jack E. Dibb, Louisa Emmons, Frank Flocke, Glen W. Sachse, David Tan, Rick Shetter, Robert W. Talbot, David G. Streets, Gregory FrostDonald Blake

Resultado de la investigación: Article

8 Citas (Scopus)

Resumen

During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to -0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 Were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx, emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx, emissions, followed by VOCs and CO. PAN as a reservoir of NOx, can contribute to a significant amount of surface ozone through thermal decomposition.

Idioma originalEnglish
Número de artículoD12S19
PublicaciónJournal of Geophysical Research Atmospheres
Volumen112
N.º12
DOI
EstadoPublished - 27 jun 2007

Huella dactilar

observation aircraft
aircraft
Ozone
ozone
Aircraft
evaluation
modeling
Troposphere
Carbon Monoxide
kriging
troposphere
direct current
boundary condition
Boundary conditions
forecasting
thermal decomposition
dry deposition
biomass burning
boundary conditions
Volatile organic compounds

ASJC Scopus subject areas

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

Citar esto

Mena-Carrasco, Marcelo ; Tang, Youhua ; Carmichael, Gregory R. ; Chai, Tianfeng ; Thongbongchoo, Narisara ; Campbell, J. Elliott ; Kulkarni, Sarika ; Horowitz, Larry ; Vukovich, Jeffrey ; Avery, Melody ; Brune, William ; Dibb, Jack E. ; Emmons, Louisa ; Flocke, Frank ; Sachse, Glen W. ; Tan, David ; Shetter, Rick ; Talbot, Robert W. ; Streets, David G. ; Frost, Gregory ; Blake, Donald. / Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation. En: Journal of Geophysical Research Atmospheres. 2007 ; Vol. 112, N.º 12.
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title = "Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation",
abstract = "During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to -0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 Were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx, emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx, emissions, followed by VOCs and CO. PAN as a reservoir of NOx, can contribute to a significant amount of surface ozone through thermal decomposition.",
author = "Marcelo Mena-Carrasco and Youhua Tang and Carmichael, {Gregory R.} and Tianfeng Chai and Narisara Thongbongchoo and Campbell, {J. Elliott} and Sarika Kulkarni and Larry Horowitz and Jeffrey Vukovich and Melody Avery and William Brune and Dibb, {Jack E.} and Louisa Emmons and Frank Flocke and Sachse, {Glen W.} and David Tan and Rick Shetter and Talbot, {Robert W.} and Streets, {David G.} and Gregory Frost and Donald Blake",
year = "2007",
month = "6",
day = "27",
doi = "10.1029/2006JD007762",
language = "English",
volume = "112",
journal = "Journal of Geophysical Research",
issn = "0148-0227",
publisher = "Wiley-Blackwell",
number = "12",

}

Mena-Carrasco, M, Tang, Y, Carmichael, GR, Chai, T, Thongbongchoo, N, Campbell, JE, Kulkarni, S, Horowitz, L, Vukovich, J, Avery, M, Brune, W, Dibb, JE, Emmons, L, Flocke, F, Sachse, GW, Tan, D, Shetter, R, Talbot, RW, Streets, DG, Frost, G & Blake, D 2007, 'Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation', Journal of Geophysical Research Atmospheres, vol. 112, n.º 12, D12S19. https://doi.org/10.1029/2006JD007762

Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation. / Mena-Carrasco, Marcelo; Tang, Youhua; Carmichael, Gregory R.; Chai, Tianfeng; Thongbongchoo, Narisara; Campbell, J. Elliott; Kulkarni, Sarika; Horowitz, Larry; Vukovich, Jeffrey; Avery, Melody; Brune, William; Dibb, Jack E.; Emmons, Louisa; Flocke, Frank; Sachse, Glen W.; Tan, David; Shetter, Rick; Talbot, Robert W.; Streets, David G.; Frost, Gregory; Blake, Donald.

En: Journal of Geophysical Research Atmospheres, Vol. 112, N.º 12, D12S19, 27.06.2007.

Resultado de la investigación: Article

TY - JOUR

T1 - Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation

AU - Mena-Carrasco, Marcelo

AU - Tang, Youhua

AU - Carmichael, Gregory R.

AU - Chai, Tianfeng

AU - Thongbongchoo, Narisara

AU - Campbell, J. Elliott

AU - Kulkarni, Sarika

AU - Horowitz, Larry

AU - Vukovich, Jeffrey

AU - Avery, Melody

AU - Brune, William

AU - Dibb, Jack E.

AU - Emmons, Louisa

AU - Flocke, Frank

AU - Sachse, Glen W.

AU - Tan, David

AU - Shetter, Rick

AU - Talbot, Robert W.

AU - Streets, David G.

AU - Frost, Gregory

AU - Blake, Donald

PY - 2007/6/27

Y1 - 2007/6/27

N2 - During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to -0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 Were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx, emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx, emissions, followed by VOCs and CO. PAN as a reservoir of NOx, can contribute to a significant amount of surface ozone through thermal decomposition.

AB - During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to -0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 Were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx, emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx, emissions, followed by VOCs and CO. PAN as a reservoir of NOx, can contribute to a significant amount of surface ozone through thermal decomposition.

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U2 - 10.1029/2006JD007762

DO - 10.1029/2006JD007762

M3 - Article

AN - SCOPUS:34547750478

VL - 112

JO - Journal of Geophysical Research

JF - Journal of Geophysical Research

SN - 0148-0227

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M1 - D12S19

ER -