SCILOV-10 Validation of SCIAMACHY limb operational NO 2 product F. Azam, K. Weigel, Ralf Bauer, A. Rozanov, M. Weber, H. Bovensmann and J. P. Burrows ESA/ESRIN, Frascati, Italy

Contents:  SCIAMACHY ESA vs IUP (datasets)  Validation Strategy  Validations: ESA/DLR - IUP Inter-comparisons Validation with occultation instruments Validation with limb instrument OSIRIS  Conclusion/Outlook 1

ESA /DLR vs IUP NO 2 : main retrieval differences 2 ESA/DLR IUP Processors: Speed Optimized Precision optimized Pre-processing no yes auxiliary spectral fits for each tangent height independently, (improves quality of spectra) Spectral range nm nm See for details; Rozanov et al, Atmos. Meas. Tech., 4, 1319–1359, 2011 Regularization Optimal regularization weak statistical parameter using L- curve regularization method (smoothness constrain) * L-curve: too strong regularization with deteriorating vertical resolution and large smoothing errors

Validation Strategy SCIAMACHY limb coverage: Profiles/day:1500 profiles for Aug Apr 2012: above 4.5 million (a single measurement is performed for four azimuths of each limb state) Data versions: ESA/DLR NO 2 version 5.02 and IUP version 3.1 Sub-sampling: ESA SCIAMACHY Sub-sampling (allows for faster computation):  Distance between two profiles is set larger than 5000 km  A profile is not allowed in the same 5° latitude band as any of 26 profiles before  Each latitude band is limited to 20% more profiles than the average 3

Validation Strategy Subsampling results in 3% of the entire datasets well distributed over all latitudes, longitudes and time ESA – IUP Collocation criteria: time = h, distance = 60 km Reason: although same measurements but the determination of the horizontal positions of the tangent point is different for both datasets. 4

Statistics 5 Dupuy et al. (2009) Mean relative difference Standard deviation of the bias corrected difference Standard error of the mean (too small to be visible on plots) Results will be shown as profiles, annual cycles and time series comparisons for 30° latitude bins.

ESA/DLR v5.02 – IUP v3.1

6 ESA/DLR vs IUP Profile comparisons Tropics Near global NH mid lat. SH mid lat. NH high lat. SH high lat. mean relative differences

7 Annual cycle 90S to 60S60N to 90N Annual cycles comparisons for high lat. show large differences in winter month (low NO 2 concentrations)

7 Time series 30S to 30N 60N to 90N90S to 60S

ESA/DLR v5.02 – Occultation instruments

 Occultation instruments and their NO2 datasets: ACE-FTS: version 3.0 ( ) HALOE: version 19 ( ) SAGE II: version 6.2 ( ) Note: SAGE II sunrise (SR) and sunset (SS) events are separately compared sunrise events suffer from instrumental problem (Bauer et al., 2012). The sunset events have a better quality but are mainly restricted to the northern mid and high latitudes ESA – Occultation instruemnts Collocation criteria: time = 6 h, distance = 1000 km 9

10 Comparisons with occultation instruments To Consider: 1)- Strong diurnal variation of NO 2 : pronounced at sunrise and sunset, SZA ≥ 90 largely effected diurnal effect error usually larger for occultation instruments below 25 km (e.g. Bauer et al., 2012 McLinden et al., 2006) a)- Changing illumination conditions (SZA) along the line of sight b)- Different instruments measure at different SZA Photochemical correction needed

11 Photochemical Correction Application:  Look up table with precalculated diurnal cycles provided by Chris McLinden, model from the University of California (McLinden et al, 2000, Prather 1992)  2 km vertical resolution and 2.5° latitude grid size.  For each collocation pair, matching geolocations and SZAs read in look- up-table  Calculation of scaling factors by dividing profile from look up table at SCIAMACHY SZA by the profile corresponding to the SZA of the other instrument  Scaling factors applied to the NO 2 profile of the other instrument Estimated errors introduced by this photochemical correction ~ 20% Bracher et al. 2005

12 To Consider: 2)- Avoid comparison of profiles at different vortex conditions and air masses  Strong horizontal gradients at the edge of the polar vortex  Modified potential vorticity (MPV) calculated from ECMWF-Interim  Profiles polewards of 35° latitude are excluded, if:  the MPV is > 30 and < 40 PVU (vortex edge)  their MPV differs by more than 3 PVU

13 ESA/DLR vs Occultation profile comparisons

14 ESA/DLR vs Occultation profile comparisons

ESA/DLR v5.02 – OSIRIS

OSIRIS version 3.0 is used. OSIRIS coverage is near global with the exception of the winter hemispheres ESA –OSIRIS Collocation criteria: time = 12 h, distance = 1000 km (OSIRIS performs measurements in a sun-synchronous orbit with an equator crossing time of the ascending node at 18:00 local solar time) Note: Based on OSIRIS comparisons with other instruments, the precision of OSIRIS NO 2 measurements is observed to be16% for 15–25 km and 6% between 25 and 35 km Reference: ( ) 15

6 ESA/DLR vs OSIRIS profile comparisons Tropics Near global NH mid lat. SH mid lat. NH high lat. SH high lat. mean relative differences

7 Time series 30S to 30N 60N to 90N90S to 60S

Summary time series plots

18 Tropics Time series

19 NH high lat. Time series

20 SH high lat. Time series

Conclusions ESA-IUP Large differences observed in the high latitude winter, elsewhere agreement within a few percents Retrieval differences (regularization) probable cause of the differences ESA-Occultation 25–35 km:- ACE-FTS ~10%, HALOE ~15% and SAGE II ~20% on the average km:- differences with the instruments may approach 50%. Below 20 km and above 40 km: large biases observed Diurnal effect error a potential dominant source of differences below 25 ESA-OSIRIS Good agreement within the precision limit of OSIRIS 21

23 Outlook/Recommendations For ESA/DLR limb NO 2, retireval should be precision optimized, studies on the choice of photochemical correction should be part of future validation activities

Extra Slides

NH mid.lat Time series

SH mid lat. Time series

Results Profile comparisons: mean relative differences plots with the standard deviation of the bias corrected differences for km Annual cycles: annual cycle vs altitude plots as monthly mean absolute amounts, monthy mean percental difference and the monthly mean percental differences for selected altitudes (20, 24, 27 and 31 km) Time Series: compared for 20–35 km on a monthly grid. For the selected altitudes (20, 24, 27 and 31 km), comparisons carried out on 30 days running averages if more than 10 collocations are found

Photochemical correction effect: Mean latitude-altitude cross section (monthly averages in 10° bins)

MPV criteria effect: