Predictability study using the Environment Canada Chemical Data Assimilation System Jean de...

Predictability study using the Environment Canada Chemical Data Assimilation System

Jean de GrandpréYves J. Rochon Richard Ménard

Air Quality Research DivisionWWOSC conference, MontréalAugust 18th 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 O3, NO2, CO, AOD …• NRT measurements: GOME-2, SBUV/2, IASI, OMPS, MODIS and

surface observations (O3, PM2.5, NO2…)

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-LINOZAssimilated observations: GOME-2, SBUV/2, MLS3D-Var Data AssimilationIndependant measurements: ACE-FTS, MIPAS,OSIRIS, OMI, …

6-hr forecast

O3 Analysis

chemObs

6-hr forecast

6-hr forecast

O3 Analysis

O3 Analysis

Multi-day Forecast

Met Analysis

Met Analysis

chemObs

chemObs

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

Anomaly correlation

n

iiicc

n

iiicfcf

i

n

iiccicfcf

MxxMxx

MxxMxxr

1

2,

1

2,

1,,

cos)(cos)(

cos)()(

fx x : Forecast and analysis values,

cx : Climatology

cfM , fx -: ( )cx over the verification area

Ozone predictability

Column Ozone predictability

Temperature anomaly correlation August 11 - Sept 5, 2003

North Hemisphere (20-90N)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10

Forecast day

3D dyn - 50 hPa

3D chem - 50 hPa

3D dyn - 70 hPa

3D chem - 70 hPa

3D dyn - 100 hPa

3D chem - 100 hPa

3D dyn - 200 hPa

3D chem - 200hPa

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

~18 000 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 = (HBHT + R)-1 (z – Hxb)

δx = BHT δQ

Q : Total column ozone analysis increment at the observation locations

xb : 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

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 – 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)

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, 2008 February, 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, 2008 February, 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 distributionTangent 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

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 2Jo/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

0.4

0.2

0.6 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