Jennifer Logan Harvard University

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Understanding the Influence of Biomass Burning on Tropospheric Ozone through Assimilation of TES data. Dylan Jones, Mark Parrington University of Toronto. Kevin Bowman, Helen Worden, John Worden, Greg Osterman Jet Propulsion Laboratory California Institute of Technology. - PowerPoint PPT Presentation

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  • Understanding the Influence of Biomass Burning on Tropospheric Ozone through Assimilation of TES dataJennifer Logan Harvard UniversityDylan Jones, Mark Parrington University of TorontoKevin Bowman, Helen Worden, John Worden, Greg OstermanJet Propulsion Laboratory California Institute of Technology

  • Impact of Biomass Burning on Tropospheric O3TES CO, 421 mb: Nov 4-17, 2004TES O3, 421 mb: Nov 5-17, 2004GEOS-Chem CO 421 mb: Nov 4-17, 2004GEOS-Chem O3, 421 mb: Nov 4-17, 2004Climatological emission inventory in the model underestimates the impact biomass burning on CO and O3 in the southern hemisphereppbppbObjective: Assess the potential of TES data to improve O3 in the model in a chemical data assimilation framework

  • Impact of Assimilation on CO and O3 (using a sequential sub-optimal Kalman filter with TES O3 and CO profile retrievals for Nov. 4-17, 2004)

    Change in O3 at 7 km (assim. - without assim.)24-hr averaged assimilated O3 at 7 km on Nov. 17(ppb CO)percentAssimilation increases CO throughout the southern hemisphereLargest increases in O3 (20-50%) are over the Indian Ocean and the Indonesian/Australian region (ppb O3)percent24-hr averaged assimilated CO at 7 km on Nov. 17Change in CO at 7 km (assim. - without assim.)

  • Assimilation of TES O3 for 1 July 2005 - 1 Jan. 2006AssimilationFree running modelO3 difference: assimilation - free running modeldata gapsMean GEOS-Chem O3 at 8 km between 20S-equator and 180W-180EIn early Sept 2005 the assimilation increases O3 by about 20% in upper troposphereDuring the 2 week data gap in September the analysis reverts to the state of the free running model

  • Comparison with Ozonesonde Data at La Reunion Island (21S, 55E)12 Oct 200517 Oct 200528 Oct 20052 Nov 2005assimilationfree running modelsondeThe ozone tropopause in GEOS-Chem is too low in Austral spring 2005 compared to the sonde data

    Assimilation of TES data reduces the bias in the model

  • Comparison of the O3 Analysis with TES Observations (350 mb)During October the assimilation reduces the bias in the model by about a factor of 2Despite the reduction in the bias, the residuals for the OmA are still large

  • Comparison of the CO Analysis with TES Observations (350 mb)Following the warm-up of the TES optical bench in Dec. 2005, the assimilation significantly reduced the bias in CO in the model In contrast to the O3 analysis, the CO OmA residuals are small, reflecting the longer lifetime of COTES OB warm-upAssimilation extended through 1 Sept 2006

  • Latitudinal Dependence of the O3 Analysis Residuals (350 mb)The assimilation has less impact in summer 2006 because we are propagating the forecast error variance without accounting for forecast error growth by summer 2006 the forecast error is about 15% in the tropics and subtropics, compared to the assumed 50% error in July 2005 Larger OmA residuals in the tropics, reflecting the shorter O3 lifetime and a lower density of TES data20S-030N-60N

  • ConclusionsAssimilation of TES O3 data produces a much improved distribution of O3 in the model, which provides greater constraints on model parameters such as the lifetime of NOx a better constraint on the NOx lifetime will result in improved estimates of NOx emissions from lightning and of the export of NOy from continental source regionsIn contrast to the CO analysis, the residuals in the O3 assimilation are large, especially in the tropics, reflecting the shorter lifetime of O3 (and the low density of the TES data) assimilating trace gases that are more chemical active than CO will be a challengeA better approach for exploiting the satellite data would be to optimize the model parameters, such as the emissions, using adjoint techniques work is needed to characterize the forecast errors across the range of chemical timescales in the model