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Predictability study using the Environment Canada Chemical Data Assimilation System

Predictability study using the Environment Canada Chemical Data Assimilation System. Jean de Grandpr é Yves J. Rochon Richard Ménard Air Quality Research Division WWOSC conference, Montr é al August 18 th 2014. Outline. Global/Regional Chemical Data Assimilation

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Predictability study using the Environment Canada Chemical Data Assimilation System

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  1. Predictability study using the Environment Canada Chemical Data Assimilation System Jean de Grandpré Yves J. Rochon Richard Ménard Air Quality Research Division WWOSC conference, Montréal August 18th 2014

  2. Outline • Global/Regional Chemical Data Assimilation • Ozone predictability and radiative coupling • Results from CDA cycles with ozone assimilation • Summary

  3. CDA for improving the Air Quality operational system (RAQDPS) • GEM-MACH as the core model • Comprehensive on-line tropospheric chemistry • Chemical Data Assimilation: 3D-Var/Envar • Assimilation of O3, NO2, CO, AOD … • NRT measurements: GOME-2, SBUV/2, IASI, OMPS, MODIS and surface observations (O3, PM2.5, NO2…) Comprehensive regional CDA system :

  4. CDA for improving the Global NWP system (GDPS) Simplified and integrated Global CDA system : • Model : On-line linearized stratospheric chemistry (GEM-LINOZ) • Assimilation of ozone, AOD and GHGs • Chemical Data Assimilation : 3D-Var/Envar • NRT measurements (GOME-2, SBUV/2, IASI, OMPS…) • Radiatively coupled model (ozone heating) • Use of ozone analyses in the NWP DA system • Produce UV-index forecasting (see poster by Y. Rochon)

  5. The Global Chemical Data Assimilation system chem Obs Met Analysis chem Obs Met Analysis chem Obs O3 Analysis O3 Analysis O3 Analysis 6-hr forecast 6-hr forecast 6-hr forecast Multi-day Forecast Multi-day Forecast Model: GEM-LINOZ Assimilated observations: GOME-2, SBUV/2, MLS 3D-Var Data Assimilation Independant measurements: ACE-FTS, MIPAS,OSIRIS, OMI, …

  6. Assimilation of ozone from MLS • GEM-Global (80 levels, lid=.1 hPa, 33km resolution) • Linearized stratospheric chemistry • 2 months assimilation cycle [winter 2009] • 3D-var Microwave Limb Sounder (EOS-AURA) Day/night measurements ~3500 profiles per day ~ 2.5 km in the vertical Vertical range : [215 - .02 hPa] V2.2 retrievals

  7. Anomaly correlation , : Forecast and analysis values : Climatology - ) : ( over the verification area

  8. Ozone predictability

  9. Column Ozone predictability

  10. Ozone radiative coupling

  11. NRT ozone measurements 6 hr sample (centered about 0 UTC) on 25 July 2008 Nadir UV-visible Spectrometer (MetOp-A) Total column amounts Day only and cloud free v8 (level-2) retrievals ~80 x 40km resolution ~18 000 measurements per day Nadir Solar Backscatter UV instrument (NOAA-17-18) 20 partial column layers ~3.2km thickness v8 (level-2) retrievals

  12. Assimilation of Total Column Ozone Background error standard deviations δQ = (HBHT + R)-1 (z – Hxb) δx = BHTδQ Q : Total column ozone analysis increment at the observation locations xb : ozone mixing ratio z : total column ozone measurements

  13. Evaluation of ozone analyses against ozone sondes: O-A (%)[January-February]MLS vs GOME-2

  14. MLS vs GOME-2

  15. MLS vs GOME-2

  16. Evaluation of ozone analyses against ozone sondes: O-A (%)[January-February]GOME-2 vs SBUV/2

  17. GOME-2 vs SBUV/2

  18. SBUV/2 Partial column retrievals Sample SBUV/2 averaging kernels at ~45 degrees V8 Partial column retrievals “y” δx = K (y – Hxb) Xb: ozone mixing ratio (80 levels) y : partial column ozone (DU) (20 levels) H : vertical integrator New partial column retrievals “z” δx = K (z – AHxb) z : partial column ozone without a priori (DU) (20 levels) A : Averaging kernels matrix (20 levels)

  19. Evaluation of SBUV/2 retrievals against ozone sondes: O-A (%)[January-February]With/Withouta priori

  20. O-A : SBUV/2 retrievals with/withouta priori

  21. SUMMARY/CONCLUSIONS • Anomaly correlation diagnostic based on total column is a useful metric for evaluating ozone analyses system. • CDA cycles using GOME-2 total column measurements and MLS observations have been compared. In the NH, O-A and O-F results are generally within 5%. The column ozone predictability for GOME-2 after 10-days is larger by ~½ day. • CDA cycles using SBUV/2 partial column measurements and GOME-2 have been compared. Results are similar in the NH but significantly worst for SBUV/2 in the SH. • The impact of using different SBUV/2 retrievals on ozone forecasts is negligible.

  22. Ozone Column (DU) July, 2008 February, 2009 Observation LINOZ - Observation

  23. Evaluation of ozone forecast against ozone sondes: O-F(10-days)[January-February]MLS vs GOME-2

  24. Ozone Column (DU) July, 2008 February, 2009 SBUV/2 - Observation LINOZ - Observation

  25. Assessment of ozone analyses/forecasts • Total column ozone (July, 2008) • Relative to OMI With SBUV/2 assimilation With GOME-2 and SBUV/2

  26. Sample ozone observation distributionTangent point orbit tracks for a 6 hour period (centered about 0 UTC) on 25 July 2008 584 1748 165-300 km along track ~ 2.5 km in the vertical (NRT: 0.2 to 68 hPa) 20 usable partial column layers with ~5 ‘no-impact’ tropo. layers ~3.2 km layers Day only Total column amounts Thinning: 1 degree separation Day only cloud free points 5502

  27. July average ozone error standard deviations (%)(before and after adjustment via Desroziers approach and 2Jo/N consideration)MLS SBUV/2 (NOAA 17) GOME-2: 1% applied SBUV/2: A priori removed before assimilation. Averaging kernels applied in assimilation. Sample SBUV/2 averaging kernels at ~45 degrees

  28. Background error standard deviations • Prescribed 6 hr ozone background error covariances • Initial values set to 5% of ozone climatology (vmr). • Adjustments to ~3-15% (of vmr) based on the Desroziers approach above =0.7 (from assimilation of MLS and using 30 degree bands). • Below =0.7: Constant extrapolation in absolute uncertainty up to a maximum of 30%. Winter Summer (ppmv) (ppmv) 0.4 0.4 0.6 0.6 0.2 0.2

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