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Predictability study using the Environment Canada Chemical Data Assimilation System Jean de Grandpré Yves J. Rochon Richard Ménard Air Quality Research.

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Presentation on theme: "Predictability study using the Environment Canada Chemical Data Assimilation System Jean de Grandpré Yves J. Rochon Richard Ménard Air Quality Research."— Presentation transcript:

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 18 th 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 O 3, NO 2, CO, AOD … NRT measurements: GOME-2, SBUV/2, IASI, OMPS, MODIS and surface observations (O 3, PM 2.5, NO 2 …) Comprehensive regional CDA system :

4 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) Simplified and integrated Global CDA system : CDA for improving the Global NWP system (GDPS)

5 The Global Chemical Data Assimilation system 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-hr forecast O 3 Analysis chem Obs 6-hr forecast 6-hr forecast O 3 Analysis O 3 Analysis Multi-day Forecast Met Analysis Met Analysis chem Obs chem Obs

6 Variational chemical data assimilation at EC slide 6 9 December 2011 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 Assimilation of ozone from MLS

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 δQ = (HBH T + R) -1 (z – Hx b ) δx = BH T δQ Q : Total column ozone analysis increment at the observation locations x b : ozone mixing ratio z : total column ozone measurements Background error standard deviations

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

14 MLS vs GOME-2

15

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

19 Evaluation of SBUV/2 retrievals against ozone sondes: O-A (%) [January-February] With/Without a priori

20 O-A : SBUV/2 retrievals with/without a 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, 2008February, 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, 2008February, 2009 SBUV/2 - Observation LINOZ - Observation

25 Variational chemical data assimilation at EC slide 25 9 December 2011 Assessment of ozone analyses/forecasts Total column ozone (July, 2008) –Relative to OMI With SBUV/2 assimilation With GOME-2 and SBUV/2

26 Variational chemical data assimilation at EC slide 26 9 December 2011

27 Variational chemical data assimilation at EC slide 27 9 December 2011

28 Variational chemical data assimilation at EC slide 28 9 December 2011 Sample ozone observation distribution Tangent point orbit tracks for a 6 hour period (centered about 0 UTC) on 25 July 2008 1748584 5502 Total column amounts Thinning: 1 degree separation Day only cloud free points 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

29 Variational chemical data assimilation at EC slide 29 9 December 2011 Sample SBUV/2 averaging kernels at ~45 degrees July average ozone error standard deviations (%) (before and after adjustment via Desroziers approach and 2J o /N consideration) MLS SBUV/2 (NOAA 17) GOME-2: 1% applied SBUV/2: A priori removed before assimilation. Averaging kernels applied in assimilation.

30 Variational chemical data assimilation at EC slide 30 9 December 2011 Winter Summer (ppmv) (ppmv) Background error standard deviations 0.4 0.2 0.6 0.4 – 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%. 0.2 Prescribed 6 hr ozone background error covariances


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