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Comparative Inverse Analysis of MOPITT and Aircraft Observations for Estimating Asian Sources of Carbon Monoxide

This study compares satellite and aircraft observations to estimate the sources of carbon monoxide in Asia. It examines the consistency and complementarity of the two datasets and evaluates their ability to constrain regional emissions. The analysis incorporates inverse modeling and quantifies the uncertainties in the observational data. The study concludes that while both satellite and aircraft observations provide valuable insights into Asian emission sources, satellite data offers greater coverage and information, but aircraft observations are essential for validation.

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Comparative Inverse Analysis of MOPITT and Aircraft Observations for Estimating Asian Sources of Carbon Monoxide

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  1. Comparative inverse analysis of MOPITT and aircraft observations to estimate Asian sources of carbon monoxide Colette Heald, Daniel Jacob, Dylan Jones, Paul Palmer, Jennifer Logan, David Streets, Glen Sachse, John Gille Spring AGU, Montreal May 20, 2004

  2. TRACE-P EMISSIONS MOPITT Do satellite and aircraft observations provide consistent/complementary/redundant constraints on pollution sources? How well does MOPITT constrain regional sources?

  3. Inverse Model Sare error covariance matrices, K is the Jacobian matrix of the forward model APPROACH: INVERSE MODEL(February-April 2001) Forward Model (GEOS-CHEM) 2°x2.5° resolution Anthropogenic CO [Streets et al., 2003] and Logan & Yevich TRACE-P Aircraft CO OBSERVATIONS EMISSIONS MOPITT CO (daily v.3 column) Biomass Burning CO [Heald et al., 2003a]

  4. MOPITT: mathematically derived result: Variance of the MOPITT/Model differences = RRE Observational Error in “MOPITT space” We also include the spatial covariance of the observational error [Jones et al., 2003] QUANTIFYING OBSERVATIONAL ERROR (SS) Aircraft:Residual Relative Error (RRE) approach [Palmer et al., 2003]: RRE Mean bias Altitude [km] SS = (y*RRE)2 (measured-model) /measured

  5. Further Insight… Effective rank of the system = SVD of There is less information in aircraft observations to constrain Asian sources MOPITT rank = 10 Aircraft rank = 5 WHAT STATE VECTOR SHOULD BE USED? Can all these regions be constrained independently by our observations? Correlation of the a posteriori errors suggest that biomass burning and anthropogenic sector emissions are correlated within any given region We reduce the state vector to 11 elements

  6. (IN)CONSISTENCY OF AM VS. PM MOPITT DATA = “best case” Night cross-over retrieval not validated – we only consider am overpass in our results

  7. S S SENSITIVITY TO ERROR SPECIFICATION Solution is sensitive to the magnitude of the observational error and its spatial correlation

  8. SENSITIVITY TO TEMPORAL AVERAGING OF MOPITT DATA Information is lost when the MOPITT observations are temporally averaged

  9. a priori (grey bar = uncertainty) “best case” inversion Ia posteriori error on “best case” I range of inverse solutions MOPITT INVERSION: RANGE OF SOLUTIONS Regions dominated by anthropogenic emissions are underestimated, Regions dominated by biomass burning emissions are overestimated. The range of solutions provides a better estimate of uncertainty than a posteriori error.

  10. COMPARING AIRCRAFT AND SATELLITE RESULTS Aircraft not well-suited to sampling all of SE Asian outflow Aircraft and MOPITT generally consistent, but differ on quantitative partitioning

  11. CONCLUSIONS • Aircraft and MOPITT provide a consistent characterization of sources in Asia. • MOPITT satellite observations provide more information towards constraining emission sources in Asia than aircraft (due more to geographical coverage of data than to data density) • BUT, aircraftobservations are essential to the science-based validation of satellite instruments, so that we can use the satellite data accurately. In addition aircraft data can provide correlative flux information • The range of inverse solutions exceeds the a posteriori uncertainty. • This range of solutions is a reduction from the a prioriuncertainty (We have improved our understanding of Asian sources) • In Asia anthropogenic emissions appear to be underestimated, while biomass burning emissions appear to be overestimated

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