1. Elena Spinei and George Mount Washington State University 1 CINDI workshop 10 - 11 March 2010

2. MAX-DOAS simulation Air Mass Factors dependence on: Wavelength Field of view Profile retrieval: Inversion procedure Aerosols Trace gases Example of NO 2 retrieval 2 CINDI workshop 10 - 11 March 2010

3. 3 Direct SunZenith SkyMulti-Axis Instrument SZA Zenith Stratospheric gas layer PBL almost equal path length through stratosphere and troposphere longer path length through stratosphere than troposphere longer path length through troposphere than stratosphere Single scattering approximation Stratospheric path is almost the same for zenith and MAX

4. bAMF = f (species profile and total abundance) Absorption > 1% Aerosols, O 3 in UV bAMF  f (species profile and total abundance) Absorption << 1% NO 2, HCHO, SO 2 *, glyoxal, One bAMF profile can be used for multiple gases and profiles under the same atmospheric conditions * Background SO 2 and low volcanic loadings CINDI workshop 10 - 11 March 2010 4 Linear CaseNon - linear Case

5. 5 CINDI workshop 10 - 11 March 2010 almost equal path length through stratosphere and troposphere at SZA < 60° al large SZA more sensitivity to lower troposphere than stratosphere week wavelength dependence (refraction)

6. 6 CINDI workshop 10 - 11 March 2010 SZA: 20°, RAA: 90°, UV: 360 nm, low aerosol loading Dependence on Viewing Zenith Angle (VZA)

7. 7 CINDI workshop 10 - 11 March 2010 SZA: 20°, RAA: 90°, VIS: 477 nm, low aerosol loading Dependence on Viewing Zenith Angle (VZA)

8. CINDI workshop 10 - 11 March 2010 8 Aerosol profiles: 477nm Aerosol profiles: 360nm Low Aerosol Loading case: Single scattering albedo 0.95 Asymmetry factor 0.70; Surface albedo 0.05 High Aerosol Loading case: Single scattering albedo 0.85 Asymmetry factor 0.67; Surface albedo 0.05

9. CINDI workshop 10 - 11 March 2010 9 Difference box AMF (Low - High aerosol loading) Box AMF for Low aerosol loading SZA: 20°, RAA: 90°, VIS: 477 nm Direct sun Zenith 2deg 5deg 10deg 15deg

10. CINDI workshop 10 - 11 March 2010 10 Difference box AMF (Low - High aerosol loading) Box AMF for Low aerosol loading SZA: 20°, RAA: 90°, UV: 360 nm

11. CINDI workshop 10 - 11 March 2010 11 Difference box AMF (Low - High aerosol loading) Box AMF for Low aerosol loading SZA: 85°, RAA: 90°, VIS: 477 nm

12. CINDI workshop 10 - 11 March 2010 12 Difference box AMF (Low - High aerosol loading) Box AMF for Low aerosol loading SZA: 85°, RAA: 90°, UV: 360 nm

13. CINDI workshop 10 - 11 March 2010 13 One wavelength 477 nm vs. Wavelength interval: 425 – 489 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case

14. CINDI workshop 10 - 11 March 2010 14 One wavelength 477 nm vs. Wavelength interval: 425 – 489 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case

15. CINDI workshop 10 - 11 March 2010 15 One wavelength 477 nm vs. Wavelength interval: 425 – 489 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case ave 425-489 nm

16. CINDI workshop 10 - 11 March 2010 16 One wavelength 360 nm vs. Wavelength interval: 337 – 380 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case

17. CINDI workshop 10 - 11 March 2010 17 One wavelength 360 nm vs. Wavelength interval: 337 – 380 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case

18. CINDI workshop 10 - 11 March 2010 18 One wavelength 360 nm vs. Wavelength interval: 337 – 380 nm VZA: 86° SZA: 20° RAA: 90° Low aerosol case ave 337-380 nm

19. CINDI workshop 10 - 11 March 2010 19 SZA: 20°, VIS: 477 nm, RAA: 90°, low aerosol case

20. CINDI workshop 10 - 11 March 2010 20 SZA: 20°, VIS: 477 nm, RAA: 90°, low aerosol case

21. CINDI workshop 10 - 11 March 2010 21 Oxygen complex (O 2 -O 2 ) absorbs in UV/VIS and easy to measure by DOAS instruments O 2 -O 2 vertical column profile proportional to the square of the O 2 concentration: Radiosonde data available for O 2 -O 2 calculations Located mainly in lower troposphere with scale height: ~4 km

22. CINDI workshop 10 - 11 March 2010 22 Measured DS SCD O4 is within 2% of the simulated using Hermans et al. cross section at room T (477 nm).

23. CINDI workshop 10 - 11 March 2010 23 Measured DS SCD O4 is within 2% of the simulated using Hermans et al. cross section at room T (477 nm).

24. CINDI workshop 10 - 11 March 2010 24 Difficult to reproduce simulated(O 2 -O 2 ) with MAX- DOAS measurements under clear sky conditions Correction factor is used (0.8-0.9). Temperature effect (O 2 -O 2 abs. cross section)? Teff varies from 274K at VZA 60  to 288K at VZA 89  (d box AMF-profile weighted) during CINDI Why do we not see this effect (up to 20%) in DS?

25. CINDI workshop 10 - 11 March 2010 25 Measurements: Δ SCD Inversion Algorithm Results: Vertical VMR profile

26. CINDI workshop 10 - 11 March 2010 26 Inverse problem: y = measured quantities F(x,b) = forward model x = unknown quantities to retrieved (state vector) b = forward model parameters, known to a certain degree ε = measurement error vector The forward model, F(x,b)estimates physical processes which relate the measured parameter (y), to (x), and (b) Ill-posed problem: NO UNIQUE SOLUTION!

27. CINDI workshop 10 - 11 March 2010 27 Optimal Estimation (Rodgers 2000): Maximum A Posteriori solution (MAP) to inverse problem Relies on a priori knowledge of the species profile (x a ) and its covariance (S a ) to constrain solution Linear Case: Gauss-Newton method (n-form) Weighting function (K) is calculated once Solution depends on measurement error (covariance S ε )

28. CINDI workshop 10 - 11 March 2010 28 Optimal Estimation (Rodgers 2000): Maximum A Posteriori solution (MAP) to inverse problem Relies on a priori knowledge of the species profile (x a ) and its covariance (S a ) to constrain solution Weighting function (K i ) is calculated at each iteration i Solution depends on measurement error (covariance S ε ) Non - linear Case: Gauss-Newton method (n-form)

29. CINDI workshop 10 - 11 March 2010 29 Three methods are currently used: Gauss-Newton method: linear case Levenberg-Marquardt method: non-linear/linear Parameterized: Assumption: NO 2 VMR and aerosol profiles can be represented by a combination of 2 Gaussian functions Constrained: VMR between 0 and 40ppb

30. CINDI workshop 10 - 11 March 2010 30 Aerosols impact light path  retrieval of trace gases depends on “correct” aerosol representation STEP I: Aerosol Inversion: O 2 O 2 MAX-DOAS measurements at 360 nm and 477 nm O 2 O 2 scale factor All scans for 1 day STEP II: Trace Gas Inversion: MAX-DOAS measurements Single vs. multiple lambdas All scans for 1 day Aerosol Ext. Coef. Profile, SSA, ASY factor, Surface Albedo LinearNon - linear

31. CINDI workshop 10 - 11 March 2010 31 Inversion Levenberg- Marquardt mod. (non-linear least sqrs fit ) and Gauss-Newton (linear solution) Inversion Levenberg- Marquardt mod. (non-linear least sqrs fit ) and Gauss-Newton (linear solution) MAX DOAS Measurements: Δ SCD ( λ, SZA, RAA, VZA) Δ SCD Error ( λ, SZA, RAA, VZA) Forward Model simulation: Measurement Vector Δ SCD ( λ, SZA, RAA, VZA) Weighting Functions K Δ SCD ( λ, SZA, RAA, VZA) On-line simulation using LIDORT v3.3 (Rob Spurr) A Priori: Profile (x a ) Profile Error (S a ) (not used for LM) Profile x i Retrieval Results: Profile Best Fit Δ SCD Covariance Matrix

32. CINDI workshop 10 - 11 March 2010 32 WinDOAS (BIRA) MFDOAS spectra corrected for dark, flat field, stray light Absorption cross sections Δ SCD error = statistical calculated by WinDOAS Trace gas Δ SCD Δ SCD at VZA Δ SCD error covariance matrix = S e diagonal elements: ( Δ SCD error) 2

33. CINDI workshop 10 - 11 March 2010 33 LIDORT v 3.3 (fast analytical calculation of intensity WFs) on-line Aerosols: extinction profile, single scattering albedo and asymmetry factor at λ (AERONET, O 4 measurements) Daily T, P profile (radiosondings) Ozone profile (climatology) and T dependent absorption cross section at λ (Bogumil et al., 2003) A priori VMR profiles and T- dependent absorption cross sections at λ (NO 2 : Vandaele et al) Surface albedo at λ (0.05) Solar zenith angle, relative azimuth angle, elevation viewing angle Box AMFs calculation from intensity WF WF Δ SCD calculation from box AMFs and air density Trace gas Δ SCD calculation Δ SCD = Σ (VMR  WF Δ SCD ) i

34. CINDI workshop 10 - 11 March 2010 34 exponential: 0.02 ext coef. at surface, scale height: 3 km S a : diagonal elements = (1 * profile OD) 2 or Off-diagonal elements = Gauss. with correlation length 0.1km Still under construction: retrieval is bias to high aerosol loading around 3-4 km. regional chemical model estimations if available (e.g. AIRPACT-3 for Pacific North- west) linear: 1 ppb at surface, 0.01 ppb at 4km S a : diagonal elements = (0.8 * profile VMR) 2 or  2 of monthly model runs; Off-diagonal elements = Gauss. with correlation length 0.1km NO 2 Aerosols

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36. CINDI workshop 10 - 11 March 2010 36 T, P profile: US standard atmosphere Ozone profile (climatology) for June at lat: 29.4° Ozone T dependent absorption cross section (Bogumil et al., 2003) Interpolation to the T profile Trace gas VMR profiles: varying on 100m grid A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km Simulated ΔSDC with and without (Gaussian noise) Solar zenith angle: 20° Relative azimuth angle: 90° Elevation viewing angles: 1, 2, 4, 5, 6, 8, 10, 15, 20, 30° (one scan) Reference: zenith from the same scan (SZA) Low Aerosol Loading: Single scattering albedo 0.95 Asymmetry factor 0.70; wavelength: 477 nm Surface albedo at λ : 0.05

37. CINDI workshop 10 - 11 March 2010 37 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

38. CINDI workshop 10 - 11 March 2010 38 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

39. CINDI workshop 10 - 11 March 2010 39 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

40. CINDI workshop 10 - 11 March 2010 40 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

41. CINDI workshop 10 - 11 March 2010 41 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

42. CINDI workshop 10 - 11 March 2010 42 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

43. CINDI workshop 10 - 11 March 2010 43 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

44. CINDI workshop 10 - 11 March 2010 44 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

45. CINDI workshop 10 - 11 March 2010 45 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

46. CINDI workshop 10 - 11 March 2010 46 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

47. CINDI workshop 10 - 11 March 2010 47 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

48. CINDI workshop 10 - 11 March 2010 48 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

49. CINDI workshop 10 - 11 March 2010 49 No noise added to simulated ΔSDC – IDEAL CASE A priori for G-N and L-M: linear from 1ppb (0km) – 0.01ppb (4km), S a scale = 1 L-M parameterized (2 Gauss): peak 1ppb, FWHM 0.1km, altitude 0.5km

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60. CINDI workshop 10 - 11 March 2010 60 L-M parameterized Gauss-Newton 23-June-2009 CINDI: AERONET derived aerosol (BIRA)

61. CINDI workshop 10 - 11 March 2010 61 L-M parameterized Gauss-Newton 30-June-2009: AERONET derived aerosol (BIRA)30-June-2009 CINDI: AERONET derived aerosol (BIRA)

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63. CINDI workshop 10 - 11 March 2010 63 MAX-DOAS produces vertical profiles of trace gas concentrations in PBL More validation required: aerosol profiles and trace gas profiles Errors on the order of a few percent to 10s %