Intercomparison of OMI NO 2 and HCHO air mass factor calculations: recommendations and best practices A. Lorente, S. Döerner, A. Hilboll, H. Yu and K. F. Boersma 19 th OMI Science Team Meeting, KNMI, De Bilt. 2 nd September 2015

What is needed? Although satellite retrievals have improved over the last decades, there is still a need to better understand the uncertainties with every retrieval step 2 QA of ECV retrieval algorithm step by step QA of complete ECV record Provide quality assured long term climate data record QA of independent reference data Harmonise, improve and quality assure independent validation data Community best practice retrieval algorithm will be applied on NO 2 and HCHO data records

Traceability chains available at: What does QA4ECV do? 3 Retrieval uncertainty dominated by AMF uncertainties Traceability chains of ECV productions Best practices to facilitate harmonization, evaluation and demonstration of traceability

What is this work about? 4 QA of ECV retrieval algorithm step by step Community best practice retrieval algorithm will be applied on NO 2 and HCHO data records Retrieval uncertainty dominated by AMF uncertainties

What is this presentation about? We evaluate different approaches to calculate AMFs by different scientific groups – Altitude dependent AMFs LUT – Tropospheric total and clear-sky AMFs for specific OMI orbit Common settings Preferred settings The objectives are: – Establish the error of forward models for UV/Vis retrievals. – Test and improve box AMF LUT for HCHO and NO 2 for QA4ECV and TROPOMI. – Overall measure of uncertainty on AMF calculation Recommendations and best practices for AMF calculation in the DOAS NO 2 and HCHO algorithm 5

AMF LUT 6 Altitude dependent AMFs at 440nm, with NO 2 absorption at 338nm with HCHO absorption Commons settings Several values of surface albedo and surface height Wide range of viewing and solar geometry Clear sky: no aerosols Rayleigh scattering, O 3 absorption.

New NO 2 AMF LUT 7 New NO 2 LUT that will be used in QA4ECV retrieval algorithm, DOMINO v3 and TROPOMI. Significant increase in reference points: chosen according to sensitivity studies of RTMs and box AMFs. From 13 x 9 x 10 x 25 x 15 x 24…… to… 16 x 11 x 10 x 26 x 14 x 174 Pressure levels 174 Surface albedo 26

NO 2 AMF LUT Correct vertical shape throughout the atmosphere Mean relative differences between DAK-SCIATRAN-LIDORT models within 2% 8 Statistical noise due to Monte Carlo simulations Higher rel. differences for extreme geometries

HCHO AMF LUT 9 Good agreement between box AMFs, although relative differences are somewhat higher than for NO 2 Comparison of TOA reflectances showed higher differences at 340 nm – Rayleigh scattering dependency with wavelength Correct vertical shape throughout the atmosphere Mean relative differences between models within 6%

NO 2 tropospheric AMFs 10 Common settings with choice for ancillary data from DOMINO V2: surface albedo (Kleipool et al. 2008) cloud information from OMI cloud retrieval temperature profile and NO 2 a priori profile (TM4) terrain height (Global 3km Digital Elevation Model data (DEM_3KM)) Cloud correction via IPA M cl = cloudy AMF; M cr = clear sky AMF; w = cloud rad. fraction Temperature correction Four specific pixels: Pixel I and pixel II: polluted regions Southern Beijing, South Korea Pixel III and IV: clean, remote locations Pacific Ocean

Agreement in clean pixels is better (0.2%) than for polluted pixels (~1.4%) TOTAL TROPOSPHERIC AMFs NO 2 tropospheric AMFs 11 Agreement is the same with and without temperature -Applying temperature correction is more realistic Pixel I: southern Beijing area

Tropospheric NO 2 AMFs: full orbit 12 First results: IASB-BIRA vs. WUR tropospheric AMFs using common settings Slope: Correlation: Points: 55343

Tropospheric NO 2 AMFs: Clear sky vs. total AMFs 13 Total AMFClear sky AMF Difference Total – clear sky AMF Cloud fraction < 0.2

Tropospheric NO 2 AMFs: Clear sky vs. total AMFs 14 Higher differences for higher cloud fraction As a function of cloud fraction: Total AMFs are higher : albedo effect Clear sky AMFs are higher: screening effect As a function of cloud pressure:

Tropospheric NO 2 AMFs: Preferred settings 15 Each group calculates AMFs with their preferred settings Which are these preferred settings? RTMs Surface albedo Kleipool et al MODIS climatology BRDF Cloud correction Terrain height Temperature profile DEM 3km Cloud information FRESCO + O2-O2 retrieval DAK LIDORT SCIATRAN McArtim IPA Cloud screening A priori profile TM4 IMAGES CTM ECMWF ERA-interim GEOS-Chem ECMWF ERA-interim

Tropospheric NO 2 AMFs: Preferred settings 16 Each group calculates AMFs with their preferred settings Project partners : WUR (KNMI), MPIC, IUP-UB, IASB-BIRA Other international groups have been invited Round robin exercise to encourage their active participation Asses similarities and differences between AMF calculation approaches Already received positive response!!

Summary and conclusions 17 Uncertainty assessment in every step of the retrieval algorithm is needed After this comparison exercise, we are able to asses best practices on NO 2 and HCHO box AMFs LUT Good agreement between box AMFs calculated by different groups (within 2% for NO 2, 6% for HCHO) Improvement of LUT for current and future missions NO 2 tropospheric AMFs: Recommendations Ancillary data: reasonable mature products Include temperature correction Other choices for cloud correction (via IPA or cloud screening), aerosol treatment are important (still under investigation, more statistics with more orbits are needed)

Back up – Reflectances TOA Reflectance as a function of: a/ Wavelengthb/ cosine of solar zenith angle Very good agreement between RTMs! 18 Differences are generally within 1% for relevant scenarios Exception occurs for large SZA

Back up – Reflectances TOA Reflectance as a function of: a/ Wavelengthb/ cosine of solar zenith angle Very good agreement between RTMs! 19 Differences are generally within 1% for relevant scenarios Exception occurs for large SZA

Back - up slides 20 REFLECTANCES Processes that might be causing differences have been investigated: GENERAL CONCLUSION Influence of all processes Layering Sphericity Rayleigh scattering  Intrinsic (light path) differences between RTMs are the most likely cause the higher differences

Back – up slide. Box AMFs at 950 hPa Differences dependency with different parameters 90% of the retrievals are done here! Relative differences within 1.5% Minor dependence of box AMFs differences with geometry parameters 21