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

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

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 :

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)

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

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 : [ hPa] V2.2 retrievals Assimilation of ozone from MLS

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

Ozone predictability

Column Ozone predictability

Ozone radiative coupling

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 ~ measurements per day Nadir Solar Backscatter UV instrument (NOAA-17-18) 20 partial column layers ~3.2km thickness v8 (level-2) retrievals

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

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

MLS vs GOME-2

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

GOME-2 vs SBUV/2

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

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

O-A : SBUV/2 retrievals with/without a priori

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.

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

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

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

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

Variational chemical data assimilation at EC slide 26 9 December 2011

Variational chemical data assimilation at EC slide 27 9 December 2011

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 Total column amounts Thinning: 1 degree separation Day only cloud free points 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

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.

Variational chemical data assimilation at EC slide 30 9 December 2011 Winter Summer (ppmv) (ppmv) Background error standard deviations – 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