1 / 19

Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI)

Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI). Xiong Liu 1,2,3 , Pawan K. Bhartia 3 , Kelly Chance 2 , Thomas P. Kurosu 2 , Robert J.D. Spurr 4 , Bojan R. Bojkov 1,3 , Ozonesonde Providers xliu@umbc.edu 1 Goddard Earth Sciences and Technology Center,UMBC

abla
Download Presentation

Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI) Xiong Liu1,2,3, Pawan K. Bhartia3, Kelly Chance2, Thomas P. Kurosu2, Robert J.D. Spurr4, Bojan R. Bojkov1,3, Ozonesonde Providers xliu@umbc.edu 1Goddard Earth Sciences and Technology Center,UMBC 2Harvard-Smithsonian Center for Astrophysics 3NASA Goddard Space Flight center 4RT Solutions Inc. 7th CMAS Conference Chapel Hill, North Carolina, October 7th, 2008

  2. Outline • Introduction • Retrieval algorithm, information content and retrieval errors • Comparison of OMI ozone profiles and stratospheric ozone column with MLS data • Comparison of OMI ozone profiles and tropospheric ozone columns with ozonesonde data • Examples of retrieved tropospheric ozone • Summary Show that the use of OMI ozone profiles as boundary conditions can significantly improve the CMAQ simulations. Pour Biazar (oral) Wang (poster)

  3. Introduction • Backscattered Ultraviolet (BUV) technique [Singer&Wentworth, 1957]: • Measure ozone profiles since the 1970s (BUV, SBUV, SBUV2) • Provide little information below 25 km [Bhartia et al., 1996]. • Tropospheric O3 Column (TOC): total O3-strat. O3 column (SOC) • Poor spatiotemporal sampling (e.g., low vertical resolution of nadir sensors and poor horizontal sampling of limb sensors) or large uncertainty in SOC • Most methods only derive monthly mean TOC in the tropics • With advanced instrumentation (OMI/MLS on AURA) and techniques (e.g., PV/trajectory mapping, assimilation), possible to derive daily TOC globally [Yang et al., 2007, Schoeberl et al., 2007; Stajner et al., 2007] • Tropospheric O3 retrievals from hyper-spectral UV instruments (e.g., GOME, OMI) [Chance et al.,1997, Munro et al.,1998, Liu et al., 2005] • Strong wavelength dependence of ozone absorption in the Hartley and Huggins bands coupled with wavelength-dependent Rayleigh scattering • Temperature dependence in the Huggins bands (313-340 nm) • We developed an 8-year (July 1995-June 2003) dataset of GOME ozone profiles and are applying our algorithm to OMI data

  4. Introduction • OMI [Levelt et al., 2006]: • Nadir-viewing UV/Visible instrument (270-500 nm) • Spatial resolution of 13×24 km2 at nadir & daily global coverage • OMI ozone profile retrieval [Liu et al., 2005] • Retrieve ozone at 24 ~2.5-km thick layers from surface to ~60 km using 270-330 nm radiances • Optimal estimation technique [Rodgers, 2000] • Use ozone profile climatology by Mcpeters et al. [2007] to constrain retrievals

  5. In practice, due to instrumental calibration error and inadequate forward modeling (e.g., aerosols, clouds), the information retrieved in the lower troposphere is significantly reduced. Retrieval Averaging Kernels • DFS: 5-8 with up to 1.5-2 in the troposphere. • Vertical resolution: ~6-8 km FWHM in the stratosphere and ~10 km in the troposphere • AKs for the bottom layer peak at this altitude. • Trop. O3 info. decreases with latitude and solar zenith angle

  6. Random (N) and Smoothing (S) Errors • Random Errors (N): <~2% above 22 km and within ~10% below • Smoothing+Random Errors: within 3% between 22-40 km, increase to 10% above 40 km, and to 20-30% below 20 km. • Errors in O3 columns (SZA < 85º) • Stratospheric O3 column: 1-2.5 DU (N), 2-5 DU (S+N) • Tropospheric O3 column: 1-3 DU (N), 2-6 DU (S+N) • Total O3 column: 0.3-2 DU (N), 0.5-4 DU (S+N)

  7. Comparison with MLS Ozone Profiles • MLS: on-board EOS-AURA, spatiotemporally coincident with OMI • MLS O3 error estimate:~5% in the strat., ~10-15% in the lower strat., ~2-3% in stratospheric O3 column [Froidevaux et al., 2007] • OMI agrees well with MLS to within their uncertainties With OMI AKs

  8. Comp. with MLS 215 hPa O3 Column • Mean bias(2006) • -0.65±2.75% (-1.8 ±7.6 DU) • O3 column above 215 hPa can be accurately derived from OMI data alone !!!

  9. Comparison with Ozonesondes • Ozonesonde data: available at AURA AVDC for August 2004-March 12, 2008 • Coincidence criteria: within 6 hours, 1º lon./lat., cloud fraction (<0.3) • Focus on two latitude bands with enough coincidences: 30ºS-30ºN, 30ºN-60ºN • Compare profile and tropospheric O3 columns (surface-200 mb, surface-~5km, surface-~2.5km) • Ozonesonde profiles are convolved with OMI averaging kernels, but not the tropospheric ozone columns

  10. Comparison with Ozonesondes (30ºS-30ºN) Solid line: mean Dashed line: 1 • Profile: within 10%, significant improvement throughout the troposphere

  11. Comparison with Ozonesondes (30ºS-30ºN) Sfc-200mb Sfc-~5km • Sfc-200 mb: –0.34.9 DU, (r=0.84), slope=0.73 • Sfc-~5 km: –0.23.5 DU, (r=0.76), slope=0.64 • Sfc-~2.5 km: –0.22.4 DU, (r=0.69), slope=0.49 Sfc-~2.5km

  12. Spring Winter Summer Fall Comparison with Ozonesondes (30ºN-60ºN) • Within 10-30%, improvement in the middle and upper troposphere. • Seasonal dependent biases.

  13. Comparison with Ozonesondes (30ºN-60ºN) Sfc-200mb Sfc-~5km • Winter: 2.87.9 DU, R = 0.65 • Spring: 2.97.3 DU, R = 0.75 • Summer: -1.65.4 DU, R = 0.79 • Fall: 1.45.2 DU, R = 0.62 Sfc-~2.5km

  14. First Layer (0-3 km) Ozone over Southeast Asia 2005m1013 2006m1021 • Enhanced ozone over Indonesia in Oct. 2006 relative to Oct. 2005. • Enhanced ozone over South China especially in Oct. 2006.

  15. Column-Averaged O3 Mixing Ratio (July 15 – September 7, 2006)

  16. Summary • Stratospheric and tropospheric O3 columns can be well derived from OMI alone. • OMI O3 profiles and stratospheric O3 column compare well with MLS, to within combined retrieval uncertainties. • OMI O3 profiles and tropospheric O3 columns generally compare well with sondes, but show seasonal/lat./alt.-dependent biases. • Retrieved tropospheric ozone can capture some signals due to pollution, biomass burning, regional and intercontinental transport, convection, and stratospheric influence. • Our product is currently a reseach product and we plan to make it an operational product. • Acknowledgements • OMI and MLS Science Teams • Support from NASA • Support from various organizations on ozonesonde observations

  17. “Boundary ozone” (0-2.5 km) Ozone over Southeast Asia 2005m10 2006m10 • Enhanced ozone over Indonesia in Oct. 2006 relative to Oct. 2005. • Enhanced ozone over South China especially in Oct. 2006.

  18. Comparison with Ozonesondes (30ºS-30ºN) Sfc-~5km A Priori W/O OMI AKs With OMI AKs

  19. Comparison with Ozonesondes (30ºN-60ºN) Sfc-~5km A Priori W/O OMI AKs With OMI AKs

More Related