QA4ECV WP3 Workshop MPIC Mainz, March Introduction

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1 QA4ECV WP3 Workshop MPIC Mainz, March 2015 Introduction Michel Van Roozendael BIRA-IASB QA4ECV WP3 Workshop MPIC Mainz, March

2 QA4ECV WP3 Tasks Objective: Provide traceable quality assurance for the independent reference data used in the validation of satellite atmospheric ECV products (NO 2, HCHO, CO) T3.5 - Establish independent Atmosphere reference data (M1-24) Collect NO 2 and HCHO reference data from MAXDOAS sites. Agree on harmonised data processing, characterisation and reporting T3.6 - Quality assurance of Atmosphere reference data (M13-30) Characterize the uncertainties of MAXDOAS NO 2 and HCHO measurements, including cloud interference and spatial representativeness effects T3.7 - Validation of Atmosphere reference data (M25-48) Validate MAXDOAS data against long-path DOAS, in-situ and NO 2 sonde QA4ECV WP3 Workshop MPIC Mainz, March

3 WP3 Deliverables No. Title Lead PM Nature Due D3.8 Historical record of independent reference data for NO 2, HCHO and CO D3.9 Quality indicators on uncertainties and representativeness of atmospheric reference data D3.10 Report on independent validation of atmospheric reference data sets BIRA-IASB 31 Other 24 IUP-UB 31 Report 30 AUTH 6 Report 48 QA4ECV WP3 Workshop MPIC Mainz, March

4 Available resources Partner Task 3.5 Task 3.6 Task 3.7 Total WP3 KNMI 4 PM 2 PM 2 PM 8 PM BIRA -UV 5 PM 1,5 PM 1 PM 7.5 PM BIRA -FTIR 5 PM 1.5 PM 1 PM 7.5 PM IUP-UB 6 PM 6 PM 2 PM 14 PM MPIC 3.5 PM 6 PM 1.5 PM 11 PM AUTH 2 PM 5 PM 2 PM 9 PM CSIC 3 PM 3.5 PM 4.5 PM 11 PM Total WP PM 25.5 PM 14 PM 68 PM M1-24 M13-30 M25-48 QA4ECV WP3 Workshop MPIC Mainz, March

5 QA4ECV reference sites FTIR sites MAXDOAS sites QA4ECV WP3 Workshop MPIC Mainz, March

6 MAXDOAS reference sites for NO 2 and HCHO MAXDOAS site Lat, Long Class Data Source De Bilt/Cabauw (NL) 52 N, 5 E Sub-urban KNMI Uccle (BE) 50 N, 4 E Urban BIRA Beijing (CHN) 40 N, 116 E Urban BIRA, MPIC Xianghe (CHN) 39 N, 117 E Sub-urban BIRA Bujumbura (BU) 3 S, 29 E Sub-urban BIRA Bremen (DE) 53 N, 9 E Urban IUP-UB Nairobi (KEN) 1 S, 37 E Rural / Urban IUP-UB Athens (GR) 38 N, 23 E Urban IUP-UB Mainz (DE) 50 N, 8 E Urban MPIC Greater Noida (IND) 28 N, 77 E Urban MPIC Thessaloniki (GR) 41 N, 23 E Urban AUTH Madrid (ESP) 40 N, 3 W Urban CSIC QA4ECV WP3 Workshop MPIC Mainz, March

7 Data availability MAXDOAS site De Bilt/Cabauw (NL) Uccle (BE) Beijing (CHN) Xianghe (CHN) Bujumbura (BU) Bremen (DE) Nairobi (KEN) Athens (GR) Mainz (DE) Greater Noida (IND) Thessaloniki (GR) Madrid (ESP) Time period QA4ECV WP3 Workshop MPIC Mainz, March

8 Overview of systems and procedures in place BIRA IUP MPIC KNMI CSIC AUTH Instrument type Own design (Xiang., Bur.), minidoas (Uccle) Slant column retrieval - Code Vertical column/profile retrieval - Product - Method - Aerosol corr - Cloud flagging - QDOAS - Profiles - OE (bepro) LIDORT - O 4 -based aerosol profile retrieval - Cloud flagging by Gielen et al. Own design (1D or 2D) - NLIN-D - Profiles - OE (BREAM) - SCIATRAN - O 4 -based aerosol correction - No cloud flag Data format HDF-GEOMS ASCII (own format) Own design (Mainz), minidoas (Beijing) - WinDOAS, MDOAS - Profiles - Param. Method - Aerosol correction - Cloug flagging by Wagner et al. HoffmannminiDOAS - Own code - Columns - DAK-based code after Vlemmix et al., Cloud ceilometer - No flags, no aerosol corr. Own design - QDOAS - Columns + surf. Conc. - SCIATRAN/ LIDORT based own code - Cloud flagging using webcam ASCII (own) ASCII (own) NetCDF (own) Own design (Avantes 2D+DS) - QDOAS - Columns - Geometric approx. - No aerosol correction - Cloud flag pyranometer data Matlab (own)

9 Issue: heterogeneity of systems Piters et al., AMT, 2012 QA4ECV WP3 Workshop MPIC Mainz, March

10 Harmonisation work plan? Review status of current systems and data evaluation procedures this workshop Standards for MAXDOAS operation (e.g. set of mandatory viewing angles) Standards for slant column fitting Standards for NO 2 and HCHO column and profile retrievals, and error/data characterization Standards for cloud flagging, and general QC? Reprocess data base using standardised procedures and assess improvement in terms of consistency QA4ECV WP3 Workshop MPIC Mainz, March

11 Use NORS legacy? Data quality indicators and data flagging Improved error characterization Improved characterization of horizontal representativeness of MAXDOAS measurements Definition/consolidation of HDF GEOMS data format Delivery on central repository (NDACC-RD) QA4ECV WP3 Workshop MPIC Mainz, March

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