1. Rossana Dragani ECMWF rossana.dragani@ecmwf.int Atmosphere: Integration of several O3-CCI products in the ERA5 system (WP3.2)

2. WP3.2: work plan Individual dataset quality assessment, experimentation and impact assessment Individual dataset quality assessment, experimentation and impact assessment TCO3 NPO3 LPO3 O3 CCI data store Algorithm Round Robin Impact vertical resolut. Impact of viewing geom. GOME-2 OMI SCIAMIPAS GOME-2 MIPAS OMI TOMS (NASA) OMI DOAS (KNMI) MIPAS (ESA) GOME-2 (O3M SAF) SCIA (KNMI) Available runs for competingalgorithms

3. Aims of WP3.2 Six (+ one optional) datasets are considered: –TCO3: SCIAMACHY, GOME, GOME-2 (+ OMI); –NPO3: GOME and GOME-2; –LPO3: MIPAS. Data assessment (for each chosen dataset): –Comparison with model equivalent (before the assimilation); –Bias characterization; –Error characterization [based on the Desroziers et al (2005) method]. Impact on the system (for each chosen dataset) RR assimilation assessments for selected datasets: –OMI, SCIA, GOME-2 TCO3; –MIPAS LPO3. User Requirements (UR): –Vertical resolution: GOME-2 TCO3 vs. NPO3; –Viewing geometry: GOME-2 NPO3 vs. MIPAS LPO3. Quality assessment Impact assessment

4. Aims of WP3.2 Six (+ one optional) datasets are considered: –TCO3: SCIAMACHY, GOME, GOME-2 (+ OMI); –NPO3: GOME and GOME-2; –LPO3: MIPAS. Data assessment (for each chosen dataset): –Comparison with model equivalent (before the assimilation); –Bias characterization; –Error characterization [based on the Desroziers et al (2005) method]. Impact on the system (for each chosen dataset) RR assimilation assessments for selected datasets: –OMI, SCIA, GOME-2 TCO3; –MIPAS LPO3. User Requirements (UR): –Vertical resolution: GOME-2 TCO3 vs. NPO3; –Viewing geometry: GOME-2 NPO3 vs. MIPAS LPO3. Quality assessment Impact assessment GOME-2 NPO3

5. Experiment set-up: Four month assimilation experiments (Jul-Oct 2008) –Except for ERS-2 GOME (Jul-Oct 1997) Impact assessment results shown for Aug-Oct only. ExperimentDescription Control L2 O3: 1 TCO3 (OMI or SCIA), SBUV 6-layer PCO3 IR/O3: HIRS [, IASI, AIRS] All other non-ozone sensitive observations PerturbationCTRL + CCI dataset to assess Perturbation 2CTRL + Alternative option of CCI dataset to assess

6. Aims of WP3.2 Six (+ one optional) datasets are considered: –TCO3: SCIAMACHY, GOME, GOME-2 (+ OMI); –NPO3: GOME and GOME-2; –LPO3: MIPAS. Data assessment (for each chosen dataset): –Comparison with model equivalent (before the assimilation); –Bias characterization; –Error characterization [based on the Desroziers et al (2005) method]. Impact on the system (for each chosen dataset) RR assimilation assessments for selected datasets: –OMI, SCIA, GOME-2 TCO3; –MIPAS LPO3. User Requirements (UR): –Vertical resolution: GOME-2 TCO3 vs. NPO3; –Viewing geometry: GOME-2 NPO3 vs. MIPAS LPO3. Quality assessment Impact assessment

7. Comparison with the model Jul-Oct 2008 Before assimilation After assimilation

8. Bias characterization Time 10-20 hPa 3-5 hPa 2-3 hPa 5-10 hPa 20-30 hPa 30-50 hPa 50-100 hPa 100-170 hPa 1. 1. 0. 2. -2. 4. -4. 2. -2. 2. -2. 2. -2. Jul-Oct 2008 Global bias correction (DU)

9. Uncertainty characterization Observation uncertainty ( o ) Estimated uncertainty ( e ) 100 *( e –  o ) / o Time Pressure Latitude s s

10. Aims of WP3.2 Six (+ one optional) datasets are considered: –TCO3: SCIAMACHY, GOME, GOME-2 (+ OMI); –NPO3: GOME and GOME-2; –LPO3: MIPAS. Data assessment (for each chosen dataset): –Comparison with model equivalent (before the assimilation); –Bias characterization; –Error characterization [based on the Desroziers et al (2005) method]. Impact on the system (for each chosen dataset) RR assimilation assessments for selected datasets: –OMI, SCIA, GOME-2 TCO3; –MIPAS LPO3. User Requirements (UR): –Vertical resolution: GOME-2 TCO3 vs. NPO3; –Viewing geometry: GOME-2 NPO3 vs. MIPAS LPO3. Quality assessment Impact assessment

11. Round-Robin assimilation: GOME2 TCO3 (1) Control Control + G2T_SAF Control + G2T_CCI Zonal Mean Temporal Mean of (MLS – Analyses)  The O3M SAF GOME2 TCO3 show almost no impact on the O3 analyses compared to Control.  The CCI GOME2 TCO3 improves the analysis fit to MLS compared to Control.

12. Round-Robin assimilation : GOME2 TCO3 (2) CTRL G2T_SAF G2T_CCI 64 232209 37 83 30-60S 60-90N 30-60N 60-90S 30S-30N RMS(Sonde-An) Number of WOUDC sondes Degradation in southern lower troposphere during winter/spring

13. UR: impact of vertical resolution GOME2 TCO3 vs GOME2 NPO3 STAT(MLS – Analyses) Perturbation – STAT(MLS – Analyses) Control Mean Std Dev CCI GOME2 TCO3 CCI GOME2 NPO3 Perturbation better Control better

14. CCI GOME-2 NPO3 impact on the rest of the system: example of consistency GOME-2 NPO3 degrades RMS of Z fc error GOME-2 NPO3 improves RMS of Z fc error Better usage of AIRS IR/O3 when GOME2 NPO3 is used.

15. UR: impact of viewing geometry: GOME2 NPO3 vs MIPAS LPO3 (1) CCI GOME2 NPO3 CCI MIPAS LPO3 STAT(MLS – Analyses) Perturbation – STAT(MLS – Analyses) Control +ve -ve +ve -ve Mean Std Dev

16. UR: impact of viewing geometry: GOME2 NPO3 vs MIPAS LPO3 (2) RMS(Sonde-An) CTRL G2 NPO3 MIPAS 64 232209 37 83 30-60S 60-90N 30-60N 60-90S 30S-30N 232

17. OMI RR: next time!  Mean(MLS – Analyses) Perturbation – Mean(MLS – Analyses) Control CCI OMI TCO3KNMI OMI TCO3 NASA OMI TCO3  All products have +ve impact in the extra-tropics compared with Control.  The CCI & NASA OMI TCO3 show stronger –ve impact on the analyses in the tropical stratosphere. +ve -ve

18. Summary and recommendations + Not assessed based on previous runs that led to –ve impact. § Data not yet available. $ Not assessed based on data assessment results (Dragani, 2012). Important to consider continuation in “NRT” of data production. TCO 3 NPO 3 LPO 3 Recommend ation GOMECCI /CCI NP GOME-2O 3 M SAFCCIO3M SAF + CCI/CCI NP SCIAKNMICCICCI § ESA $ CCI OMIKNMINASACCICCI § /KNMI MIPAS//ESACCI