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Atmosphere: Integration of several O3-CCI products in the ERA5 system (WP3.2)

Atmosphere: Integration of several O3-CCI products in the ERA5 system (WP3.2). Rossana Dragani ECMWF rossana.dragani@ecmwf.int. WP3.2: work plan. NPO3. TCO3. LPO3. O3 CCI data store. OMI TOMS (NASA). OMI DOAS (KNMI). MIPAS (ESA). SCIA (KNMI). GOME-2 (O3M SAF). Available runs for

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Atmosphere: Integration of several O3-CCI products in the ERA5 system (WP3.2)

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

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

  3. Aims of WP3.2 Quality assessment • 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. Impact assessment

  4. Aims of WP3.2 Quality assessment GOME-2 NPO3 • 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-2TCO3 vs. NPO3; • Viewing geometry: GOME-2 NPO3 vs. MIPAS LPO3. Impact assessment

  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.

  6. Aims of WP3.2 Quality assessment • 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. Impact assessment

  7. Comparison with the model <Observation> Jul-Oct 2008 <Background> <Analyses> Before assimilation After assimilation

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

  9. Uncertainty characterization 100 *(se– so) / so s Observation uncertainty (so) Pressure Latitude Estimated uncertainty (se) s Latitude Time

  10. Aims of WP3.2 Quality assessment • 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. Impact assessment

  11. Round-Robin assimilation: GOME2 TCO3 (1) Control Control + G2T_CCI Control + G2T_SAF • 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. Zonal Mean Temporal Mean of (MLS – Analyses)

  12. Round-Robin assimilation : GOME2 TCO3 (2) 60-90N 30S-30N 30-60N 232 209 64 60-90S 30-60S CTRL G2T_SAF G2T_CCI Number of WOUDC sondes Degradation in southern lower troposphere during winter/spring 83 37 RMS(Sonde-An)

  13. UR: impact of vertical resolutionGOME2 TCO3 vs GOME2 NPO3 CCI GOME2 TCO3 CCI GOME2 NPO3 Control better Mean Perturbation better Std Dev STAT(MLS – Analyses)Perturbation – STAT(MLS – Analyses)Control

  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 MIPAS LPO3 CCI GOME2 NPO3 -ve Mean +ve -ve Std Dev +ve STAT(MLS – Analyses)Perturbation – STAT(MLS – Analyses)Control

  16. UR: impact of viewing geometry:GOME2 NPO3 vs MIPAS LPO3 (2) 30-60N 30S-30N 60-90N 232 209 64 60-90S 30-60S CTRL G2 NPO3 MIPAS 232 83 37 RMS(Sonde-An)

  17. OMI RR: next time!  KNMI OMI TCO3 CCI OMI TCO3 -ve +ve 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. Mean(MLS – Analyses)Perturbation – Mean(MLS – Analyses)Control

  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.

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